�ݺ�ߣshows by User: ToineBogers

�ݺ�ߣshows by User: ToineBogers / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: ToineBogers / Mon, 24 Mar 2025 06:02:33 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: ToineBogers From Queries to Candidates: Exploring the Search and Source Interaction Behavior of Recruiters /slideshow/from-queries-to-candidates-exploring-the-search-and-source-interaction-behavior-of-recruiters/277113618 chiir2025-rich-log-analysis-250324060233-2db4b7eb
Recruitment is a professional search domain that has been largely overlooked in IR research, even though better support of recruiters could have a big impact on job seekers, companies and society as a whole. In this paper, we analyze the search formulation and source selection behavior of the recruiters at one of Scandinavia’s largest job portals and recruitment agencies using search logs for close to 18,000 recruitment search tasks. We provide an analysis of the search sessions of recruiters in terms search tactics, query operators, query length, term re-use and filter usage, and break down their behavior both by task type and task complexity. We also relate their short-term tactics to different learning stages in the search process and investigate their influence on search success. We find that identifying and assessing relevant candidates for a job posting is a complex task: recruiters usually submit multiple queries during sessions that can last for hours and that increase in complexity. Recruiters all spend more time per query as their session progresses. We also observed query reformulation strategies that indicate distinct patterns of knowledge gaining during sessions. Relating these tactics to positive responses from candidates we aim at predicting successful strategies. (Paper presentation @ CHIIR 2025, Melbourne, Australia) Link to paper: TBA]]>
Recruitment is a professional search domain that has been largely overlooked in IR research, even though better support of recruiters could have a big impact on job seekers, companies and society as a whole. In this paper, we analyze the search formulation and source selection behavior of the recruiters at one of Scandinavia’s largest job portals and recruitment agencies using search logs for close to 18,000 recruitment search tasks. We provide an analysis of the search sessions of recruiters in terms search tactics, query operators, query length, term re-use and filter usage, and break down their behavior both by task type and task complexity. We also relate their short-term tactics to different learning stages in the search process and investigate their influence on search success. We find that identifying and assessing relevant candidates for a job posting is a complex task: recruiters usually submit multiple queries during sessions that can last for hours and that increase in complexity. Recruiters all spend more time per query as their session progresses. We also observed query reformulation strategies that indicate distinct patterns of knowledge gaining during sessions. Relating these tactics to positive responses from candidates we aim at predicting successful strategies. (Paper presentation @ CHIIR 2025, Melbourne, Australia) Link to paper: TBA]]> Mon, 24 Mar 2025 06:02:33 GMT /slideshow/from-queries-to-candidates-exploring-the-search-and-source-interaction-behavior-of-recruiters/277113618 ToineBogers@slideshare.net(ToineBogers) From Queries to Candidates: Exploring the Search and Source Interaction Behavior of Recruiters ToineBogers Recruitment is a professional search domain that has been largely overlooked in IR research, even though better support of recruiters could have a big impact on job seekers, companies and society as a whole. In this paper, we analyze the search formulation and source selection behavior of the recruiters at one of Scandinavia’s largest job portals and recruitment agencies using search logs for close to 18,000 recruitment search tasks. We provide an analysis of the search sessions of recruiters in terms search tactics, query operators, query length, term re-use and filter usage, and break down their behavior both by task type and task complexity. We also relate their short-term tactics to different learning stages in the search process and investigate their influence on search success. We find that identifying and assessing relevant candidates for a job posting is a complex task: recruiters usually submit multiple queries during sessions that can last for hours and that increase in complexity. Recruiters all spend more time per query as their session progresses. We also observed query reformulation strategies that indicate distinct patterns of knowledge gaining during sessions. Relating these tactics to positive responses from candidates we aim at predicting successful strategies. (Paper presentation @ CHIIR 2025, Melbourne, Australia) Link to paper: TBA <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/chiir2025-rich-log-analysis-250324060233-2db4b7eb-thumbnail.jpg?width=120&height=120&fit=bounds" /> Recruitment is a professional search domain that has been largely overlooked in IR research, even though better support of recruiters could have a big impact on job seekers, companies and society as a whole. In this paper, we analyze the search formulation and source selection behavior of the recruiters at one of Scandinavia’s largest job portals and recruitment agencies using search logs for close to 18,000 recruitment search tasks. We provide an analysis of the search sessions of recruiters in terms search tactics, query operators, query length, term re-use and filter usage, and break down their behavior both by task type and task complexity. We also relate their short-term tactics to different learning stages in the search process and investigate their influence on search success. We find that identifying and assessing relevant candidates for a job posting is a complex task: recruiters usually submit multiple queries during sessions that can last for hours and that increase in complexity. Recruiters all spend more time per query as their session progresses. We also observed query reformulation strategies that indicate distinct patterns of knowledge gaining during sessions. Relating these tactics to positive responses from candidates we aim at predicting successful strategies. (Paper presentation @ CHIIR 2025, Melbourne, Australia) Link to paper: TBA

From Queries to Candidates: Exploring the Search and Source Interaction Behavior of Recruiters from Toine Bogers

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0 "If I like BLANK, what else will I like?": Analyzing a Human Recommendation Community on Reddit /slideshow/if-i-like-blank-what-else-will-i-like-analyzing-a-human-recommendation-community-on-reddit/267286294 iconf2024-if-you-like-blank-240416123240-f6d3e96f
While there have been several studies on how users experience algorithmic recommendations and their explanations, we know relatively little about human recommendations and which item aspects humans highlight when describing their own recommendation needs. A better understanding of human recommendation behavior could help us design better recommender systems that are more attuned to their users. In this paper, we take a step towards such understanding by analyzing a Reddit community dedicated to requesting and providing for recommendations: /r/ifyoulikeblank. After a general analysis of the community, we provide a more detailed analysis of the prevalent music requests and the example items used to ask for these recommendations. Finally, we compare these human recommendations to algorithmic recommendations to better char- acterize their differences. We conclude by discussing the implications of our work for recommender systems design.]]>
While there have been several studies on how users experience algorithmic recommendations and their explanations, we know relatively little about human recommendations and which item aspects humans highlight when describing their own recommendation needs. A better understanding of human recommendation behavior could help us design better recommender systems that are more attuned to their users. In this paper, we take a step towards such understanding by analyzing a Reddit community dedicated to requesting and providing for recommendations: /r/ifyoulikeblank. After a general analysis of the community, we provide a more detailed analysis of the prevalent music requests and the example items used to ask for these recommendations. Finally, we compare these human recommendations to algorithmic recommendations to better char- acterize their differences. We conclude by discussing the implications of our work for recommender systems design.]]> Tue, 16 Apr 2024 12:32:40 GMT /slideshow/if-i-like-blank-what-else-will-i-like-analyzing-a-human-recommendation-community-on-reddit/267286294 ToineBogers@slideshare.net(ToineBogers) "If I like BLANK, what else will I like?": Analyzing a Human Recommendation Community on Reddit ToineBogers While there have been several studies on how users experience algorithmic recommendations and their explanations, we know relatively little about human recommendations and which item aspects humans highlight when describing their own recommendation needs. A better understanding of human recommendation behavior could help us design better recommender systems that are more attuned to their users. In this paper, we take a step towards such understanding by analyzing a Reddit community dedicated to requesting and providing for recommendations: /r/ifyoulikeblank. After a general analysis of the community, we provide a more detailed analysis of the prevalent music requests and the example items used to ask for these recommendations. Finally, we compare these human recommendations to algorithmic recommendations to better char- acterize their differences. We conclude by discussing the implications of our work for recommender systems design. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/iconf2024-if-you-like-blank-240416123240-f6d3e96f-thumbnail.jpg?width=120&height=120&fit=bounds" /> While there have been several studies on how users experience algorithmic recommendations and their explanations, we know relatively little about human recommendations and which item aspects humans highlight when describing their own recommendation needs. A better understanding of human recommendation behavior could help us design better recommender systems that are more attuned to their users. In this paper, we take a step towards such understanding by analyzing a Reddit community dedicated to requesting and providing for recommendations: /r/ifyoulikeblank. After a general analysis of the community, we provide a more detailed analysis of the prevalent music requests and the example items used to ask for these recommendations. Finally, we compare these human recommendations to algorithmic recommendations to better char- acterize their differences. We conclude by discussing the implications of our work for recommender systems design.

"If I like BLANK, what else will I like?": Analyzing a Human Recommendation Community on Reddit from Toine Bogers

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0 Hands-free but not Eyes-free: A Usability Evaluation of Siri while Driving /slideshow/handsfree-but-not-eyesfree-a-usability-evaluation-of-siri-while-driving/230402227 siri-while-driving-200317153207
Distractions while driving are a major cause of traffic accidents and chief among these is the use of mobile phones. Driver distractions typically fall into four categories-visual, cognitive, bio-mechanical, and auditory-and different technological solutions have been proposed to address these. Intelligent Personal Assistants (IPAs), such as Siri, is a recent example of such a technological solution that offers the potential for hands-free phone interaction through a voice-controlled interface. IPAs could potentially reduce visual and bio-mechanical distractions if they are usable enough to not increase a driver's cognitive load. We present the results of a controlled experiment with the aim of understanding how the use of Siri while driving compares to manual interaction in terms of usability and distractions. We also tested these two interaction types in the lab in order to understand how the main driving task influences Siri's (perceived) usability. Our study shows that Siri is not ready for every-day use in the car: interacting with Siri while driving is likely to be unsafe for most participants, especially less experienced drivers. Participants were distracted by Siri due to its over-reliance on visual feedback as well as frequent time-outs by Siri when waiting for a response from a driver occupied with the road environment. Speech recognition quality in a noisy car as well as problematic multi-lingual speech recognition in general are other issues that resulted in low usability and more cognitive distractions. While interacting with Siri may be hands-free, it does not provide an eyes-free and distraction-free experience yet. (Planned paper presentation @ CHIIR 2020, Vancouver, Canada) Link to paper: https://dl.acm.org/doi/abs/10.1145/3343413.3377962 Link to YouTube video of recorded presentation: https://youtu.be/5uR_z2R_Y6Y]]>
Distractions while driving are a major cause of traffic accidents and chief among these is the use of mobile phones. Driver distractions typically fall into four categories-visual, cognitive, bio-mechanical, and auditory-and different technological solutions have been proposed to address these. Intelligent Personal Assistants (IPAs), such as Siri, is a recent example of such a technological solution that offers the potential for hands-free phone interaction through a voice-controlled interface. IPAs could potentially reduce visual and bio-mechanical distractions if they are usable enough to not increase a driver's cognitive load. We present the results of a controlled experiment with the aim of understanding how the use of Siri while driving compares to manual interaction in terms of usability and distractions. We also tested these two interaction types in the lab in order to understand how the main driving task influences Siri's (perceived) usability. Our study shows that Siri is not ready for every-day use in the car: interacting with Siri while driving is likely to be unsafe for most participants, especially less experienced drivers. Participants were distracted by Siri due to its over-reliance on visual feedback as well as frequent time-outs by Siri when waiting for a response from a driver occupied with the road environment. Speech recognition quality in a noisy car as well as problematic multi-lingual speech recognition in general are other issues that resulted in low usability and more cognitive distractions. While interacting with Siri may be hands-free, it does not provide an eyes-free and distraction-free experience yet. (Planned paper presentation @ CHIIR 2020, Vancouver, Canada) Link to paper: https://dl.acm.org/doi/abs/10.1145/3343413.3377962 Link to YouTube video of recorded presentation: https://youtu.be/5uR_z2R_Y6Y]]> Tue, 17 Mar 2020 15:32:07 GMT /slideshow/handsfree-but-not-eyesfree-a-usability-evaluation-of-siri-while-driving/230402227 ToineBogers@slideshare.net(ToineBogers) Hands-free but not Eyes-free: A Usability Evaluation of Siri while Driving ToineBogers Distractions while driving are a major cause of traffic accidents and chief among these is the use of mobile phones. Driver distractions typically fall into four categories-visual, cognitive, bio-mechanical, and auditory-and different technological solutions have been proposed to address these. Intelligent Personal Assistants (IPAs), such as Siri, is a recent example of such a technological solution that offers the potential for hands-free phone interaction through a voice-controlled interface. IPAs could potentially reduce visual and bio-mechanical distractions if they are usable enough to not increase a driver's cognitive load. We present the results of a controlled experiment with the aim of understanding how the use of Siri while driving compares to manual interaction in terms of usability and distractions. We also tested these two interaction types in the lab in order to understand how the main driving task influences Siri's (perceived) usability. Our study shows that Siri is not ready for every-day use in the car: interacting with Siri while driving is likely to be unsafe for most participants, especially less experienced drivers. Participants were distracted by Siri due to its over-reliance on visual feedback as well as frequent time-outs by Siri when waiting for a response from a driver occupied with the road environment. Speech recognition quality in a noisy car as well as problematic multi-lingual speech recognition in general are other issues that resulted in low usability and more cognitive distractions. While interacting with Siri may be hands-free, it does not provide an eyes-free and distraction-free experience yet. (Planned paper presentation @ CHIIR 2020, Vancouver, Canada) Link to paper: https://dl.acm.org/doi/abs/10.1145/3343413.3377962 Link to YouTube video of recorded presentation: https://youtu.be/5uR_z2R_Y6Y <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/siri-while-driving-200317153207-thumbnail.jpg?width=120&height=120&fit=bounds" /> Distractions while driving are a major cause of traffic accidents and chief among these is the use of mobile phones. Driver distractions typically fall into four categories-visual, cognitive, bio-mechanical, and auditory-and different technological solutions have been proposed to address these. Intelligent Personal Assistants (IPAs), such as Siri, is a recent example of such a technological solution that offers the potential for hands-free phone interaction through a voice-controlled interface. IPAs could potentially reduce visual and bio-mechanical distractions if they are usable enough to not increase a driver's cognitive load. We present the results of a controlled experiment with the aim of understanding how the use of Siri while driving compares to manual interaction in terms of usability and distractions. We also tested these two interaction types in the lab in order to understand how the main driving task influences Siri's (perceived) usability. Our study shows that Siri is not ready for every-day use in the car: interacting with Siri while driving is likely to be unsafe for most participants, especially less experienced drivers. Participants were distracted by Siri due to its over-reliance on visual feedback as well as frequent time-outs by Siri when waiting for a response from a driver occupied with the road environment. Speech recognition quality in a noisy car as well as problematic multi-lingual speech recognition in general are other issues that resulted in low usability and more cognitive distractions. While interacting with Siri may be hands-free, it does not provide an eyes-free and distraction-free experience yet. (Planned paper presentation @ CHIIR 2020, Vancouver, Canada) Link to paper: https://dl.acm.org/doi/abs/10.1145/3343413.3377962 Link to YouTube video of recorded presentation: https://youtu.be/5uR_z2R_Y6Y

Hands-free but not Eyes-free: A Usability Evaluation of Siri while Driving from Toine Bogers

]]> 316 0 https://cdn.slidesharecdn.com/ss_thumbnails/siri-while-driving-200317153207-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 “Looking for an Amazing Game I Can Relax and Sink Hours into...”: A Study of Relevance Aspects in Video Game Discovery /ToineBogers/looking-for-an-amazing-game-i-can-relax-and-sink-hours-into-a-study-of-relevance-aspects-in-video-game-discovery iconf2019-rel-games-2019-04-01-190402131620
With the rapid growth of the video game industry over the past decade, there has been a commensurate increase in research activity focused on a variety of aspects of video games. How people discover the video games they want to play and how they articulate these information needs is still largely unknown, however. A better understanding of video game-related information needs and what makes a game relevant to a user could aid in the design of more effective, domain-specific search engines. In this paper we take a first step towards such domain-specific understanding. We present an analysis of a random sample of 521 complex game requests posted on Reddit. A coding scheme was developed that captures the 41 different aspects of relevance and information needs expressed in these requests. We find that game requests contain an aver- age of close to 5 different relevance aspects. Several of these relevance aspects are geared specifically to video games, while others are more general. (Paper presentation @ iConference 2019, College Park, MD)]]>
With the rapid growth of the video game industry over the past decade, there has been a commensurate increase in research activity focused on a variety of aspects of video games. How people discover the video games they want to play and how they articulate these information needs is still largely unknown, however. A better understanding of video game-related information needs and what makes a game relevant to a user could aid in the design of more effective, domain-specific search engines. In this paper we take a first step towards such domain-specific understanding. We present an analysis of a random sample of 521 complex game requests posted on Reddit. A coding scheme was developed that captures the 41 different aspects of relevance and information needs expressed in these requests. We find that game requests contain an aver- age of close to 5 different relevance aspects. Several of these relevance aspects are geared specifically to video games, while others are more general. (Paper presentation @ iConference 2019, College Park, MD)]]> Tue, 02 Apr 2019 13:16:20 GMT /ToineBogers/looking-for-an-amazing-game-i-can-relax-and-sink-hours-into-a-study-of-relevance-aspects-in-video-game-discovery ToineBogers@slideshare.net(ToineBogers) “Looking for an Amazing Game I Can Relax and Sink Hours into...”: A Study of Relevance Aspects in Video Game Discovery ToineBogers With the rapid growth of the video game industry over the past decade, there has been a commensurate increase in research activity focused on a variety of aspects of video games. How people discover the video games they want to play and how they articulate these information needs is still largely unknown, however. A better understanding of video game-related information needs and what makes a game relevant to a user could aid in the design of more effective, domain-specific search engines. In this paper we take a first step towards such domain-specific understanding. We present an analysis of a random sample of 521 complex game requests posted on Reddit. A coding scheme was developed that captures the 41 different aspects of relevance and information needs expressed in these requests. We find that game requests contain an aver- age of close to 5 different relevance aspects. Several of these relevance aspects are geared specifically to video games, while others are more general. (Paper presentation @ iConference 2019, College Park, MD) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/iconf2019-rel-games-2019-04-01-190402131620-thumbnail.jpg?width=120&height=120&fit=bounds" /> With the rapid growth of the video game industry over the past decade, there has been a commensurate increase in research activity focused on a variety of aspects of video games. How people discover the video games they want to play and how they articulate these information needs is still largely unknown, however. A better understanding of video game-related information needs and what makes a game relevant to a user could aid in the design of more effective, domain-specific search engines. In this paper we take a first step towards such domain-specific understanding. We present an analysis of a random sample of 521 complex game requests posted on Reddit. A coding scheme was developed that captures the 41 different aspects of relevance and information needs expressed in these requests. We find that game requests contain an aver- age of close to 5 different relevance aspects. Several of these relevance aspects are geared specifically to video games, while others are more general. (Paper presentation @ iConference 2019, College Park, MD)

“Looking for an Amazing Game I Can Relax and Sink Hours into...”: A Study of Relevance Aspects in Video Game Discovery from Toine Bogers

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0 A Study of Usage and Usability of Intelligent Personal Assistants in Denmark /slideshow/a-study-of-usage-and-usability-of-intelligent-personal-assistants-in-denmark-139116595/139116595 iconf2019-siri-190401181617
Intelligent personal assistants (IPA), such as Siri, Google Assistant, Alexa, and Cortana, are rapidly becoming a popular way of interacting with our smart devices. As a result, there has been a wealth of research on all aspects of IPAs in recent years, such as studies of usage of and user satisfaction with IPAs. However, the overwhelming majority of these studies have focused on English as the interaction language. In this paper, we investigate the usage and perceived usability of IPAs in Denmark. We conduct a questionnaire with 357 Danish-speaking respondents that sheds light on how IPAs are used in Denmark. We find they are only used regularly by 19.9% of respondents and that most people do not find IPAs to be reliable. We also conduct a usability study of Siri and find that Siri suffers from several issues when used in Danish: poor voice recognition, unnatural dialogue responses, and an inability to support mixed-language speech recognition. Our findings shed light on both the current state of usage and adoption of IPAs in Denmark as well as the usability of its most popular IPA in a foreign-language setting. (Paper presentation @ iConference 2019, College Park, MD)]]>
Intelligent personal assistants (IPA), such as Siri, Google Assistant, Alexa, and Cortana, are rapidly becoming a popular way of interacting with our smart devices. As a result, there has been a wealth of research on all aspects of IPAs in recent years, such as studies of usage of and user satisfaction with IPAs. However, the overwhelming majority of these studies have focused on English as the interaction language. In this paper, we investigate the usage and perceived usability of IPAs in Denmark. We conduct a questionnaire with 357 Danish-speaking respondents that sheds light on how IPAs are used in Denmark. We find they are only used regularly by 19.9% of respondents and that most people do not find IPAs to be reliable. We also conduct a usability study of Siri and find that Siri suffers from several issues when used in Danish: poor voice recognition, unnatural dialogue responses, and an inability to support mixed-language speech recognition. Our findings shed light on both the current state of usage and adoption of IPAs in Denmark as well as the usability of its most popular IPA in a foreign-language setting. (Paper presentation @ iConference 2019, College Park, MD)]]> Mon, 01 Apr 2019 18:16:17 GMT /slideshow/a-study-of-usage-and-usability-of-intelligent-personal-assistants-in-denmark-139116595/139116595 ToineBogers@slideshare.net(ToineBogers) A Study of Usage and Usability of Intelligent Personal Assistants in Denmark ToineBogers Intelligent personal assistants (IPA), such as Siri, Google Assistant, Alexa, and Cortana, are rapidly becoming a popular way of interacting with our smart devices. As a result, there has been a wealth of research on all aspects of IPAs in recent years, such as studies of usage of and user satisfaction with IPAs. However, the overwhelming majority of these studies have focused on English as the interaction language. In this paper, we investigate the usage and perceived usability of IPAs in Denmark. We conduct a questionnaire with 357 Danish-speaking respondents that sheds light on how IPAs are used in Denmark. We find they are only used regularly by 19.9% of respondents and that most people do not find IPAs to be reliable. We also conduct a usability study of Siri and find that Siri suffers from several issues when used in Danish: poor voice recognition, unnatural dialogue responses, and an inability to support mixed-language speech recognition. Our findings shed light on both the current state of usage and adoption of IPAs in Denmark as well as the usability of its most popular IPA in a foreign-language setting. (Paper presentation @ iConference 2019, College Park, MD) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/iconf2019-siri-190401181617-thumbnail.jpg?width=120&height=120&fit=bounds" /> Intelligent personal assistants (IPA), such as Siri, Google Assistant, Alexa, and Cortana, are rapidly becoming a popular way of interacting with our smart devices. As a result, there has been a wealth of research on all aspects of IPAs in recent years, such as studies of usage of and user satisfaction with IPAs. However, the overwhelming majority of these studies have focused on English as the interaction language. In this paper, we investigate the usage and perceived usability of IPAs in Denmark. We conduct a questionnaire with 357 Danish-speaking respondents that sheds light on how IPAs are used in Denmark. We find they are only used regularly by 19.9% of respondents and that most people do not find IPAs to be reliable. We also conduct a usability study of Siri and find that Siri suffers from several issues when used in Danish: poor voice recognition, unnatural dialogue responses, and an inability to support mixed-language speech recognition. Our findings shed light on both the current state of usage and adoption of IPAs in Denmark as well as the usability of its most popular IPA in a foreign-language setting. (Paper presentation @ iConference 2019, College Park, MD)

A Study of Usage and Usability of Intelligent Personal Assistants in Denmark from Toine Bogers

]]> 293 4 https://cdn.slidesharecdn.com/ss_thumbnails/iconf2019-siri-190401181617-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 “What was this movie about this chick?”: A Comparative Study of Relevance Aspects in Book and Movie Discovery /slideshow/what-was-this-movie-about-this-chick-a-comparative-study-of-relevance-aspects-in-book-and-movie-discovery/91945211 iconf2018-rel-aspects-v4-180326124051
In recent decades, information retrieval research has slowly expanded its focus to address the wealth of complex search requests present in our work and leisure environments. A better understanding of such complex needs could aid in the design of more effective, domain-specific search engines. In this paper we take a first step towards such domain-specific understanding. We present an analysis of a random sample of 1000+ complex book and movie search requests posted in the LibraryThing and Internet Movie Database forums. A coding scheme was developed that captures the 29 different relevance aspects expressed in these requests. We find that while the identified relevance aspects are remarkably similar for complex book and movie requests, their relative occurrence does vary considerably from domain to domain. (Paper presentation @ iConference 2018, Sheffield, UK)]]>
In recent decades, information retrieval research has slowly expanded its focus to address the wealth of complex search requests present in our work and leisure environments. A better understanding of such complex needs could aid in the design of more effective, domain-specific search engines. In this paper we take a first step towards such domain-specific understanding. We present an analysis of a random sample of 1000+ complex book and movie search requests posted in the LibraryThing and Internet Movie Database forums. A coding scheme was developed that captures the 29 different relevance aspects expressed in these requests. We find that while the identified relevance aspects are remarkably similar for complex book and movie requests, their relative occurrence does vary considerably from domain to domain. (Paper presentation @ iConference 2018, Sheffield, UK)]]> Mon, 26 Mar 2018 12:40:51 GMT /slideshow/what-was-this-movie-about-this-chick-a-comparative-study-of-relevance-aspects-in-book-and-movie-discovery/91945211 ToineBogers@slideshare.net(ToineBogers) “What was this movie about this chick?”: A Comparative Study of Relevance Aspects in Book and Movie Discovery ToineBogers In recent decades, information retrieval research has slowly expanded its focus to address the wealth of complex search requests present in our work and leisure environments. A better understanding of such complex needs could aid in the design of more effective, domain-specific search engines. In this paper we take a first step towards such domain-specific understanding. We present an analysis of a random sample of 1000+ complex book and movie search requests posted in the LibraryThing and Internet Movie Database forums. A coding scheme was developed that captures the 29 different relevance aspects expressed in these requests. We find that while the identified relevance aspects are remarkably similar for complex book and movie requests, their relative occurrence does vary considerably from domain to domain. (Paper presentation @ iConference 2018, Sheffield, UK) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/iconf2018-rel-aspects-v4-180326124051-thumbnail.jpg?width=120&height=120&fit=bounds" /> In recent decades, information retrieval research has slowly expanded its focus to address the wealth of complex search requests present in our work and leisure environments. A better understanding of such complex needs could aid in the design of more effective, domain-specific search engines. In this paper we take a first step towards such domain-specific understanding. We present an analysis of a random sample of 1000+ complex book and movie search requests posted in the LibraryThing and Internet Movie Database forums. A coding scheme was developed that captures the 29 different relevance aspects expressed in these requests. We find that while the identified relevance aspects are remarkably similar for complex book and movie requests, their relative occurrence does vary considerably from domain to domain. (Paper presentation @ iConference 2018, Sheffield, UK)

“What was this movie about this chick?”: A Comparative Study of Relevance Aspects in Book and Movie Discovery from Toine Bogers

]]> 405 1 https://cdn.slidesharecdn.com/ss_thumbnails/iconf2018-rel-aspects-v4-180326124051-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 "I just scroll through my stuff until I find it or give up": A Contextual Inquiry of PIM on Private Handheld Devices /slideshow/i-just-scroll-through-my-stuff-until-i-find-it-or-give-up-a-contextual-inquiry-of-pim-on-private-handheld-devices/90663925 chiir2018-handheld-pim-180314162407
While ownership and usage of handheld devices such as smartphones and tablets continues to grow at a rapid pace, we do not have complete picture of how people manage personal information on these devices. The few existing studies have typically used interview or survey methods to focus on personal information management (PIM) practices on smartphones. We present the results of an exploratory contextual inquiry study of PIM practices aimed at providing a structured, naturalistic overview of PIM on both smartphones and tablets. We find that people use multiple complementary strategies to acquire different types of information on their devices, and that people rely strongly on automatic chronological ordering instead of organization by subject, although this pays off most for smaller information collections. Deletion of information is strongly influenced by usefulness and personal attachment. Finally, we find that people strongly prefer browsing over search when retrieving information from their devices. (Paper presentation @ CHIIR 2018, New Brunswick, NJ)]]>
While ownership and usage of handheld devices such as smartphones and tablets continues to grow at a rapid pace, we do not have complete picture of how people manage personal information on these devices. The few existing studies have typically used interview or survey methods to focus on personal information management (PIM) practices on smartphones. We present the results of an exploratory contextual inquiry study of PIM practices aimed at providing a structured, naturalistic overview of PIM on both smartphones and tablets. We find that people use multiple complementary strategies to acquire different types of information on their devices, and that people rely strongly on automatic chronological ordering instead of organization by subject, although this pays off most for smaller information collections. Deletion of information is strongly influenced by usefulness and personal attachment. Finally, we find that people strongly prefer browsing over search when retrieving information from their devices. (Paper presentation @ CHIIR 2018, New Brunswick, NJ)]]> Wed, 14 Mar 2018 16:24:06 GMT /slideshow/i-just-scroll-through-my-stuff-until-i-find-it-or-give-up-a-contextual-inquiry-of-pim-on-private-handheld-devices/90663925 ToineBogers@slideshare.net(ToineBogers) "I just scroll through my stuff until I find it or give up": A Contextual Inquiry of PIM on Private Handheld Devices ToineBogers While ownership and usage of handheld devices such as smartphones and tablets continues to grow at a rapid pace, we do not have complete picture of how people manage personal information on these devices. The few existing studies have typically used interview or survey methods to focus on personal information management (PIM) practices on smartphones. We present the results of an exploratory contextual inquiry study of PIM practices aimed at providing a structured, naturalistic overview of PIM on both smartphones and tablets. We find that people use multiple complementary strategies to acquire different types of information on their devices, and that people rely strongly on automatic chronological ordering instead of organization by subject, although this pays off most for smaller information collections. Deletion of information is strongly influenced by usefulness and personal attachment. Finally, we find that people strongly prefer browsing over search when retrieving information from their devices. (Paper presentation @ CHIIR 2018, New Brunswick, NJ) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/chiir2018-handheld-pim-180314162407-thumbnail.jpg?width=120&height=120&fit=bounds" /> While ownership and usage of handheld devices such as smartphones and tablets continues to grow at a rapid pace, we do not have complete picture of how people manage personal information on these devices. The few existing studies have typically used interview or survey methods to focus on personal information management (PIM) practices on smartphones. We present the results of an exploratory contextual inquiry study of PIM practices aimed at providing a structured, naturalistic overview of PIM on both smartphones and tablets. We find that people use multiple complementary strategies to acquire different types of information on their devices, and that people rely strongly on automatic chronological ordering instead of organization by subject, although this pays off most for smaller information collections. Deletion of information is strongly influenced by usefulness and personal attachment. Finally, we find that people strongly prefer browsing over search when retrieving information from their devices. (Paper presentation @ CHIIR 2018, New Brunswick, NJ)

"I just scroll through my stuff until I find it or give up": A Contextual Inquiry of PIM on Private Handheld Devices from Toine Bogers

]]> 128 3 https://cdn.slidesharecdn.com/ss_thumbnails/chiir2018-handheld-pim-180314162407-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 Natural Language Processing /slideshow/natural-language-processing-87921780/87921780 quartz-nlp-slides-180213104519
This lectures provides students with an introduction to natural language processing, with a specific focus on the basics of two applications: vector semantics and text classification. (Lecture at the QUARTZ PhD Winter School (http://www.quartz-itn.eu/training/winter-school/ in Padua, Italy on February 12, 2018)]]>
This lectures provides students with an introduction to natural language processing, with a specific focus on the basics of two applications: vector semantics and text classification. (Lecture at the QUARTZ PhD Winter School (http://www.quartz-itn.eu/training/winter-school/ in Padua, Italy on February 12, 2018)]]> Tue, 13 Feb 2018 10:45:19 GMT /slideshow/natural-language-processing-87921780/87921780 ToineBogers@slideshare.net(ToineBogers) Natural Language Processing ToineBogers This lectures provides students with an introduction to natural language processing, with a specific focus on the basics of two applications: vector semantics and text classification. (Lecture at the QUARTZ PhD Winter School (http://www.quartz-itn.eu/training/winter-school/ in Padua, Italy on February 12, 2018) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/quartz-nlp-slides-180213104519-thumbnail.jpg?width=120&height=120&fit=bounds" /> This lectures provides students with an introduction to natural language processing, with a specific focus on the basics of two applications: vector semantics and text classification. (Lecture at the QUARTZ PhD Winter School (http://www.quartz-itn.eu/training/winter-school/ in Padua, Italy on February 12, 2018)

Natural Language Processing from Toine Bogers

]]> 948 9 https://cdn.slidesharecdn.com/ss_thumbnails/quartz-nlp-slides-180213104519-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 Defining and Supporting Narrative-driven Recommendation /slideshow/defining-and-supporting-narrativedriven-recommendation/79279650 recsys2017-narrative-170830091101
Research into recommendation algorithms has made great strides in recent years. However, these algorithms are typically applied in relatively straightforward scenarios: given information about a user’s past preferences, what will they like in the future? Recommendation is often more complex: evaluating recommended items never takes place in a vacuum, and it is often a single step in the user’s more complex background task. In this paper, we define a specific type of recommendation scenario called narrative-driven recommendation, where the recommendation process is driven by both a log of the user’s past transactions as well as a narrative description of their current interest(s). Through an analysis of a set of real-world recommendation narratives from the LibraryThing forums, we demonstrate the uniqueness and richness of this scenario and highlight common patterns and properties of such narratives. (Paper presentation @ RecSys 2017, Como, Italy)]]>
Research into recommendation algorithms has made great strides in recent years. However, these algorithms are typically applied in relatively straightforward scenarios: given information about a user’s past preferences, what will they like in the future? Recommendation is often more complex: evaluating recommended items never takes place in a vacuum, and it is often a single step in the user’s more complex background task. In this paper, we define a specific type of recommendation scenario called narrative-driven recommendation, where the recommendation process is driven by both a log of the user’s past transactions as well as a narrative description of their current interest(s). Through an analysis of a set of real-world recommendation narratives from the LibraryThing forums, we demonstrate the uniqueness and richness of this scenario and highlight common patterns and properties of such narratives. (Paper presentation @ RecSys 2017, Como, Italy)]]> Wed, 30 Aug 2017 09:11:00 GMT /slideshow/defining-and-supporting-narrativedriven-recommendation/79279650 ToineBogers@slideshare.net(ToineBogers) Defining and Supporting Narrative-driven Recommendation ToineBogers Research into recommendation algorithms has made great strides in recent years. However, these algorithms are typically applied in relatively straightforward scenarios: given information about a user’s past preferences, what will they like in the future? Recommendation is often more complex: evaluating recommended items never takes place in a vacuum, and it is often a single step in the user’s more complex background task. In this paper, we define a specific type of recommendation scenario called narrative-driven recommendation, where the recommendation process is driven by both a log of the user’s past transactions as well as a narrative description of their current interest(s). Through an analysis of a set of real-world recommendation narratives from the LibraryThing forums, we demonstrate the uniqueness and richness of this scenario and highlight common patterns and properties of such narratives. (Paper presentation @ RecSys 2017, Como, Italy) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/recsys2017-narrative-170830091101-thumbnail.jpg?width=120&height=120&fit=bounds" /> Research into recommendation algorithms has made great strides in recent years. However, these algorithms are typically applied in relatively straightforward scenarios: given information about a user’s past preferences, what will they like in the future? Recommendation is often more complex: evaluating recommended items never takes place in a vacuum, and it is often a single step in the user’s more complex background task. In this paper, we define a specific type of recommendation scenario called narrative-driven recommendation, where the recommendation process is driven by both a log of the user’s past transactions as well as a narrative description of their current interest(s). Through an analysis of a set of real-world recommendation narratives from the LibraryThing forums, we demonstrate the uniqueness and richness of this scenario and highlight common patterns and properties of such narratives. (Paper presentation @ RecSys 2017, Como, Italy)

Defining and Supporting Narrative-driven Recommendation from Toine Bogers

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0 An In-depth Analysis of Tags and Controlled Metadata for Book Search /slideshow/an-indepth-analysis-of-tags-and-controlled-metadata-for-book-search/73546654 iconf2017-tags-cv-170323160046
Book search for information needs that go beyond standard bibliographic data is far from a solved problem. Such complex information needs often cover a combination of different aspects, such as specific genres or plot elements, engagement or novelty. By design, subject information in controlled vocabularies is not always adequate in covering such complex needs, and social tags have been proposed as an alternative. In this paper we present a large-scale empirical comparison and in-depth analysis of the value of controlled vocabularies and tags for book retrieval using a test collection of over 2 million book records and over 330 real-world book information needs. We find that while tags and controlled vocabulary terms provide complementary performance, tags perform better overall. However, this is not due to a popularity effect; instead, tags are better at matching the language of regular users. Finally, we perform a detailed failure analysis and show, using tags and controlled vocabulary terms, that some request types are inherently more diffcult to solve than others. (Paper presentation @ iConference 2017, Wuhan, China)]]>
Book search for information needs that go beyond standard bibliographic data is far from a solved problem. Such complex information needs often cover a combination of different aspects, such as specific genres or plot elements, engagement or novelty. By design, subject information in controlled vocabularies is not always adequate in covering such complex needs, and social tags have been proposed as an alternative. In this paper we present a large-scale empirical comparison and in-depth analysis of the value of controlled vocabularies and tags for book retrieval using a test collection of over 2 million book records and over 330 real-world book information needs. We find that while tags and controlled vocabulary terms provide complementary performance, tags perform better overall. However, this is not due to a popularity effect; instead, tags are better at matching the language of regular users. Finally, we perform a detailed failure analysis and show, using tags and controlled vocabulary terms, that some request types are inherently more diffcult to solve than others. (Paper presentation @ iConference 2017, Wuhan, China)]]> Thu, 23 Mar 2017 16:00:46 GMT /slideshow/an-indepth-analysis-of-tags-and-controlled-metadata-for-book-search/73546654 ToineBogers@slideshare.net(ToineBogers) An In-depth Analysis of Tags and Controlled Metadata for Book Search ToineBogers Book search for information needs that go beyond standard bibliographic data is far from a solved problem. Such complex information needs often cover a combination of different aspects, such as specific genres or plot elements, engagement or novelty. By design, subject information in controlled vocabularies is not always adequate in covering such complex needs, and social tags have been proposed as an alternative. In this paper we present a large-scale empirical comparison and in-depth analysis of the value of controlled vocabularies and tags for book retrieval using a test collection of over 2 million book records and over 330 real-world book information needs. We find that while tags and controlled vocabulary terms provide complementary performance, tags perform better overall. However, this is not due to a popularity effect; instead, tags are better at matching the language of regular users. Finally, we perform a detailed failure analysis and show, using tags and controlled vocabulary terms, that some request types are inherently more diffcult to solve than others. (Paper presentation @ iConference 2017, Wuhan, China) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/iconf2017-tags-cv-170323160046-thumbnail.jpg?width=120&height=120&fit=bounds" /> Book search for information needs that go beyond standard bibliographic data is far from a solved problem. Such complex information needs often cover a combination of different aspects, such as specific genres or plot elements, engagement or novelty. By design, subject information in controlled vocabularies is not always adequate in covering such complex needs, and social tags have been proposed as an alternative. In this paper we present a large-scale empirical comparison and in-depth analysis of the value of controlled vocabularies and tags for book retrieval using a test collection of over 2 million book records and over 330 real-world book information needs. We find that while tags and controlled vocabulary terms provide complementary performance, tags perform better overall. However, this is not due to a popularity effect; instead, tags are better at matching the language of regular users. Finally, we perform a detailed failure analysis and show, using tags and controlled vocabulary terms, that some request types are inherently more diffcult to solve than others. (Paper presentation @ iConference 2017, Wuhan, China)

An In-depth Analysis of Tags and Controlled Metadata for Book Search from Toine Bogers

]]> 269 2 https://cdn.slidesharecdn.com/ss_thumbnails/iconf2017-tags-cv-170323160046-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 Personalized search /slideshow/personalized-search/62181814 personalized-search-160519115443
An introductory presentation about the current state of personalization in (Web) search for Bibliotekarforbundet's series of 'gå-hjem-møder'. Presented on May 17, 2016 at Aalborg University Copenhagen.]]>
An introductory presentation about the current state of personalization in (Web) search for Bibliotekarforbundet's series of 'gå-hjem-møder'. Presented on May 17, 2016 at Aalborg University Copenhagen.]]> Thu, 19 May 2016 11:54:43 GMT /slideshow/personalized-search/62181814 ToineBogers@slideshare.net(ToineBogers) Personalized search ToineBogers An introductory presentation about the current state of personalization in (Web) search for Bibliotekarforbundet's series of 'gå-hjem-møder'. Presented on May 17, 2016 at Aalborg University Copenhagen. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/personalized-search-160519115443-thumbnail.jpg?width=120&height=120&fit=bounds" /> An introductory presentation about the current state of personalization in (Web) search for Bibliotekarforbundet's series of 'gå-hjem-møder'. Presented on May 17, 2016 at Aalborg University Copenhagen.

Personalized search from Toine Bogers

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0 A Longitudinal Analysis of Search Engine Index Size /slideshow/a-longitudinal-analysis-of-search-engine-index-size/50090762 issi2015-index-size-estimation-150702113426-lva1-app6892
]]>
]]> Thu, 02 Jul 2015 11:34:26 GMT /slideshow/a-longitudinal-analysis-of-search-engine-index-size/50090762 ToineBogers@slideshare.net(ToineBogers) A Longitudinal Analysis of Search Engine Index Size ToineBogers <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/issi2015-index-size-estimation-150702113426-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" />

A Longitudinal Analysis of Search Engine Index Size from Toine Bogers

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0 Tagging vs. Controlled Vocabulary: Which is More Helpful for Book Search? /slideshow/tagging-vs-controlled-vocabulary-which-is-more-helpful-for-book-search/46347885 tagging-vs-controlled-vocabulary-150327002746-conversion-gate01
The popularity of social tagging has sparked a great deal of debate on whether tags could replace or improve upon professional metadata as descriptors of books and other information objects. In this paper we present a large-scale empirical comparison of the contributions of individual information elements like core bibliographic data, controlled vocabulary terms, reviews, and tags to the retrieval performance. Our comparison is done using a test collection of over 2 million book records with information elements from Amazon, the British Library, the Library of Congress, and LibraryThing. We find that tags and controlled vocabulary terms do not actually outperform each other consistently, but seem to provide complementary contributions: some information needs are best addressed using controlled vocabulary terms whereas other are best addressed using tags. (Paper presentation @ iConference 2015, Newport Beach)]]>
The popularity of social tagging has sparked a great deal of debate on whether tags could replace or improve upon professional metadata as descriptors of books and other information objects. In this paper we present a large-scale empirical comparison of the contributions of individual information elements like core bibliographic data, controlled vocabulary terms, reviews, and tags to the retrieval performance. Our comparison is done using a test collection of over 2 million book records with information elements from Amazon, the British Library, the Library of Congress, and LibraryThing. We find that tags and controlled vocabulary terms do not actually outperform each other consistently, but seem to provide complementary contributions: some information needs are best addressed using controlled vocabulary terms whereas other are best addressed using tags. (Paper presentation @ iConference 2015, Newport Beach)]]> Fri, 27 Mar 2015 00:27:45 GMT /slideshow/tagging-vs-controlled-vocabulary-which-is-more-helpful-for-book-search/46347885 ToineBogers@slideshare.net(ToineBogers) Tagging vs. Controlled Vocabulary: Which is More Helpful for Book Search? ToineBogers The popularity of social tagging has sparked a great deal of debate on whether tags could replace or improve upon professional metadata as descriptors of books and other information objects. In this paper we present a large-scale empirical comparison of the contributions of individual information elements like core bibliographic data, controlled vocabulary terms, reviews, and tags to the retrieval performance. Our comparison is done using a test collection of over 2 million book records with information elements from Amazon, the British Library, the Library of Congress, and LibraryThing. We find that tags and controlled vocabulary terms do not actually outperform each other consistently, but seem to provide complementary contributions: some information needs are best addressed using controlled vocabulary terms whereas other are best addressed using tags. (Paper presentation @ iConference 2015, Newport Beach) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/tagging-vs-controlled-vocabulary-150327002746-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /> The popularity of social tagging has sparked a great deal of debate on whether tags could replace or improve upon professional metadata as descriptors of books and other information objects. In this paper we present a large-scale empirical comparison of the contributions of individual information elements like core bibliographic data, controlled vocabulary terms, reviews, and tags to the retrieval performance. Our comparison is done using a test collection of over 2 million book records with information elements from Amazon, the British Library, the Library of Congress, and LibraryThing. We find that tags and controlled vocabulary terms do not actually outperform each other consistently, but seem to provide complementary contributions: some information needs are best addressed using controlled vocabulary terms whereas other are best addressed using tags. (Paper presentation @ iConference 2015, Newport Beach)

Tagging vs. Controlled Vocabulary: Which is More Helpful for Book Search? from Toine Bogers

]]> 687 5 https://cdn.slidesharecdn.com/ss_thumbnails/tagging-vs-controlled-vocabulary-150327002746-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 Measuring System Performance in Cultural Heritage Systems /slideshow/mmeasuring-systemperformanceprintversion/46244773 measuring-system-performance-150324192536-conversion-gate01
This talk presents a high-level overview of the different components of cultural heritage information systems—search, browsing, recommendation, and enrichment—and their evaluation, and the common challenges. (Invited talk at the "Evaluating Cultural Heritage Information Systems" workshop at the iConference 2015 in Newport Beach, CA)]]>
This talk presents a high-level overview of the different components of cultural heritage information systems—search, browsing, recommendation, and enrichment—and their evaluation, and the common challenges. (Invited talk at the "Evaluating Cultural Heritage Information Systems" workshop at the iConference 2015 in Newport Beach, CA)]]> Tue, 24 Mar 2015 19:25:36 GMT /slideshow/mmeasuring-systemperformanceprintversion/46244773 ToineBogers@slideshare.net(ToineBogers) Measuring System Performance in Cultural Heritage Systems ToineBogers This talk presents a high-level overview of the different components of cultural heritage information systems—search, browsing, recommendation, and enrichment—and their evaluation, and the common challenges. (Invited talk at the "Evaluating Cultural Heritage Information Systems" workshop at the iConference 2015 in Newport Beach, CA) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/measuring-system-performance-150324192536-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /> This talk presents a high-level overview of the different components of cultural heritage information systems—search, browsing, recommendation, and enrichment—and their evaluation, and the common challenges. (Invited talk at the "Evaluating Cultural Heritage Information Systems" workshop at the iConference 2015 in Newport Beach, CA)

Measuring System Performance in Cultural Heritage Systems from Toine Bogers

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0 How 'Social' are Social News Sites? Exploring the Motivations for Using Reddit.com /slideshow/how-social-are-social-news-sites-exploring-the-motivations-for-using-redditcom/31983902 iconf2014-social-news-140306051355-phpapp02
Social news sites allow their users to submit and vote on online news stories, thereby bypassing the authority and power of traditional newspaper editors. In this paper we explore what motivates users of social news sites, such as Reddit, to participate in this collaborative editorial process. We present a tiered framework of motivational factors for participating on social news sites, based on a comprehensive literature review, drawn from fields like social media research, sociology, (social) psychology, and behavioral economics. We then validate this framework through a survey deployed on Reddit and use the results of this survey to focus the motivational framework for the social news domain. The recreational value of the information posted to Reddit, along with the powerful possibilities for customization appear to be the most powerful incentives for using Reddit. Perhaps surprisingly, the social aspect of social news sites is not a motivating factor for the majority of Reddit users. Influencing the placement and reception of news stories in their niche communities of interest is what draws people to sites such as Reddit. (Paper presentation @ iConference 2014, Berlin)]]>
Social news sites allow their users to submit and vote on online news stories, thereby bypassing the authority and power of traditional newspaper editors. In this paper we explore what motivates users of social news sites, such as Reddit, to participate in this collaborative editorial process. We present a tiered framework of motivational factors for participating on social news sites, based on a comprehensive literature review, drawn from fields like social media research, sociology, (social) psychology, and behavioral economics. We then validate this framework through a survey deployed on Reddit and use the results of this survey to focus the motivational framework for the social news domain. The recreational value of the information posted to Reddit, along with the powerful possibilities for customization appear to be the most powerful incentives for using Reddit. Perhaps surprisingly, the social aspect of social news sites is not a motivating factor for the majority of Reddit users. Influencing the placement and reception of news stories in their niche communities of interest is what draws people to sites such as Reddit. (Paper presentation @ iConference 2014, Berlin)]]> Thu, 06 Mar 2014 05:13:55 GMT /slideshow/how-social-are-social-news-sites-exploring-the-motivations-for-using-redditcom/31983902 ToineBogers@slideshare.net(ToineBogers) How 'Social' are Social News Sites? Exploring the Motivations for Using Reddit.com ToineBogers Social news sites allow their users to submit and vote on online news stories, thereby bypassing the authority and power of traditional newspaper editors. In this paper we explore what motivates users of social news sites, such as Reddit, to participate in this collaborative editorial process. We present a tiered framework of motivational factors for participating on social news sites, based on a comprehensive literature review, drawn from fields like social media research, sociology, (social) psychology, and behavioral economics. We then validate this framework through a survey deployed on Reddit and use the results of this survey to focus the motivational framework for the social news domain. The recreational value of the information posted to Reddit, along with the powerful possibilities for customization appear to be the most powerful incentives for using Reddit. Perhaps surprisingly, the social aspect of social news sites is not a motivating factor for the majority of Reddit users. Influencing the placement and reception of news stories in their niche communities of interest is what draws people to sites such as Reddit. (Paper presentation @ iConference 2014, Berlin) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/iconf2014-social-news-140306051355-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Social news sites allow their users to submit and vote on online news stories, thereby bypassing the authority and power of traditional newspaper editors. In this paper we explore what motivates users of social news sites, such as Reddit, to participate in this collaborative editorial process. We present a tiered framework of motivational factors for participating on social news sites, based on a comprehensive literature review, drawn from fields like social media research, sociology, (social) psychology, and behavioral economics. We then validate this framework through a survey deployed on Reddit and use the results of this survey to focus the motivational framework for the social news domain. The recreational value of the information posted to Reddit, along with the powerful possibilities for customization appear to be the most powerful incentives for using Reddit. Perhaps surprisingly, the social aspect of social news sites is not a motivating factor for the majority of Reddit users. Influencing the placement and reception of news stories in their niche communities of interest is what draws people to sites such as Reddit. (Paper presentation @ iConference 2014, Berlin)

How 'Social' are Social News Sites? Exploring the Motivations for Using Reddit.com from Toine Bogers

]]> 717 7 https://cdn.slidesharecdn.com/ss_thumbnails/iconf2014-social-news-140306051355-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 Search & Recommendation: Birds of a Feather? /slideshow/mind-thegaptalksingleslides/31938906 mind-the-gap-talk-140305071543-phpapp02
In just a little over half a century, the field of information retrieval has experienced spectacular growth and success, with IR applications such as search engines becoming a billion-dollar industry in the past decades. Recommender systems have seen an even more meteoric rise to success with wide-scale application by companies like Amazon, Facebook, and Netflix. But are search and recommendation really two different fields of research that address different problems with different sets of algorithms in papers published at distinct conferences? In my talk, I want to argue that search and recommendation are more similar than they have been treated in the past decade. By looking more closely at the tasks and problems that search and recommendation try to solve, at the algorithms used to solve these problems and at the way their performance is evaluated, I want to show that there is no clear black and white division between the two. Instead, search and recommendation are part of a much more fluid continuum of methods and techniques for information access. (Keynote at "Mind The Gap '14" workshop at the iConference 2014 in Berlin, Germany)]]>
In just a little over half a century, the field of information retrieval has experienced spectacular growth and success, with IR applications such as search engines becoming a billion-dollar industry in the past decades. Recommender systems have seen an even more meteoric rise to success with wide-scale application by companies like Amazon, Facebook, and Netflix. But are search and recommendation really two different fields of research that address different problems with different sets of algorithms in papers published at distinct conferences? In my talk, I want to argue that search and recommendation are more similar than they have been treated in the past decade. By looking more closely at the tasks and problems that search and recommendation try to solve, at the algorithms used to solve these problems and at the way their performance is evaluated, I want to show that there is no clear black and white division between the two. Instead, search and recommendation are part of a much more fluid continuum of methods and techniques for information access. (Keynote at "Mind The Gap '14" workshop at the iConference 2014 in Berlin, Germany)]]> Wed, 05 Mar 2014 07:15:43 GMT /slideshow/mind-thegaptalksingleslides/31938906 ToineBogers@slideshare.net(ToineBogers) Search & Recommendation: Birds of a Feather? ToineBogers In just a little over half a century, the field of information retrieval has experienced spectacular growth and success, with IR applications such as search engines becoming a billion-dollar industry in the past decades. Recommender systems have seen an even more meteoric rise to success with wide-scale application by companies like Amazon, Facebook, and Netflix. But are search and recommendation really two different fields of research that address different problems with different sets of algorithms in papers published at distinct conferences? In my talk, I want to argue that search and recommendation are more similar than they have been treated in the past decade. By looking more closely at the tasks and problems that search and recommendation try to solve, at the algorithms used to solve these problems and at the way their performance is evaluated, I want to show that there is no clear black and white division between the two. Instead, search and recommendation are part of a much more fluid continuum of methods and techniques for information access. (Keynote at "Mind The Gap '14" workshop at the iConference 2014 in Berlin, Germany) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mind-the-gap-talk-140305071543-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> In just a little over half a century, the field of information retrieval has experienced spectacular growth and success, with IR applications such as search engines becoming a billion-dollar industry in the past decades. Recommender systems have seen an even more meteoric rise to success with wide-scale application by companies like Amazon, Facebook, and Netflix. But are search and recommendation really two different fields of research that address different problems with different sets of algorithms in papers published at distinct conferences? In my talk, I want to argue that search and recommendation are more similar than they have been treated in the past decade. By looking more closely at the tasks and problems that search and recommendation try to solve, at the algorithms used to solve these problems and at the way their performance is evaluated, I want to show that there is no clear black and white division between the two. Instead, search and recommendation are part of a much more fluid continuum of methods and techniques for information access. (Keynote at "Mind The Gap '14" workshop at the iConference 2014 in Berlin, Germany)

Search & Recommendation: Birds of a Feather? from Toine Bogers

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0 Micro-Serendipity: Meaningful Coincidences in Everyday Life Shared on Twitter /slideshow/microserendipity/27711117 iconf2013-twitter-serendipity-131029180133-phpapp01
In this paper we present work on micro-serendipity: investigating everyday contexts, conditions, and attributes of serendipity as shared on Twitter. In contrast to related work, we deliberately omit a preset definition of serendipity to allow for the inclusion of micro- occurrences of what people themselves consider as meaningful coincidences in everyday life. We find that different people have different thresholds for what they consider serendipitous, revealing a serendipity continuum. We propose a distinction between background serendipity (or ‘traditional’ serendipity) and foreground serendipity (or ‘synchronicity’, unexpectedly finding something meaningful related to foreground interests). Our study confirms the presence of three key serendipity elements of unexpectedness, insight and value, and suggests a fourth element, preoccupation (foreground problem/interest), which covers synchronicity. Finally, we find that a combination of features based on word usage, POS categories, and hashtag usage show promise in automatically identifying tweets about serendipitous occurrences.]]>
In this paper we present work on micro-serendipity: investigating everyday contexts, conditions, and attributes of serendipity as shared on Twitter. In contrast to related work, we deliberately omit a preset definition of serendipity to allow for the inclusion of micro- occurrences of what people themselves consider as meaningful coincidences in everyday life. We find that different people have different thresholds for what they consider serendipitous, revealing a serendipity continuum. We propose a distinction between background serendipity (or ‘traditional’ serendipity) and foreground serendipity (or ‘synchronicity’, unexpectedly finding something meaningful related to foreground interests). Our study confirms the presence of three key serendipity elements of unexpectedness, insight and value, and suggests a fourth element, preoccupation (foreground problem/interest), which covers synchronicity. Finally, we find that a combination of features based on word usage, POS categories, and hashtag usage show promise in automatically identifying tweets about serendipitous occurrences.]]> Tue, 29 Oct 2013 18:01:32 GMT /slideshow/microserendipity/27711117 ToineBogers@slideshare.net(ToineBogers) Micro-Serendipity: Meaningful Coincidences in Everyday Life Shared on Twitter ToineBogers In this paper we present work on micro-serendipity: investigating everyday contexts, conditions, and attributes of serendipity as shared on Twitter. In contrast to related work, we deliberately omit a preset definition of serendipity to allow for the inclusion of micro- occurrences of what people themselves consider as meaningful coincidences in everyday life. We find that different people have different thresholds for what they consider serendipitous, revealing a serendipity continuum. We propose a distinction between background serendipity (or ‘traditional’ serendipity) and foreground serendipity (or ‘synchronicity’, unexpectedly finding something meaningful related to foreground interests). Our study confirms the presence of three key serendipity elements of unexpectedness, insight and value, and suggests a fourth element, preoccupation (foreground problem/interest), which covers synchronicity. Finally, we find that a combination of features based on word usage, POS categories, and hashtag usage show promise in automatically identifying tweets about serendipitous occurrences. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/iconf2013-twitter-serendipity-131029180133-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> In this paper we present work on micro-serendipity: investigating everyday contexts, conditions, and attributes of serendipity as shared on Twitter. In contrast to related work, we deliberately omit a preset definition of serendipity to allow for the inclusion of micro- occurrences of what people themselves consider as meaningful coincidences in everyday life. We find that different people have different thresholds for what they consider serendipitous, revealing a serendipity continuum. We propose a distinction between background serendipity (or ‘traditional’ serendipity) and foreground serendipity (or ‘synchronicity’, unexpectedly finding something meaningful related to foreground interests). Our study confirms the presence of three key serendipity elements of unexpectedness, insight and value, and suggests a fourth element, preoccupation (foreground problem/interest), which covers synchronicity. Finally, we find that a combination of features based on word usage, POS categories, and hashtag usage show promise in automatically identifying tweets about serendipitous occurrences.

Micro-Serendipity: Meaningful Coincidences in Everyday Life Shared on Twitter from Toine Bogers

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0 Benchmarking Domain-specific Expert Search using Workshop Program Committees /slideshow/benchmarking-27710760/27710760 bordea2013-slides-131029174601-phpapp02
Traditionally, relevance assessments for expert search have been gathered through self-assessment or based on the opinions of co-workers. We introduce three benchmark datasets for expert search that use conference workshops for relevance assessment. Our data sets cover entire research domains as opposed to single institutions. In addition, they provide a larger number of topic-person associations and allow a more objective and fine-grained evaluation of expertise than existing data sets do. We present and discuss baseline results for a language modelling and a topic-centric approach to expert search. We find that the topic-centric approach achieves the best results on domain-specific datasets. Presented at CSTA workshop, CIKM 2013, October 28, 2013]]>
Traditionally, relevance assessments for expert search have been gathered through self-assessment or based on the opinions of co-workers. We introduce three benchmark datasets for expert search that use conference workshops for relevance assessment. Our data sets cover entire research domains as opposed to single institutions. In addition, they provide a larger number of topic-person associations and allow a more objective and fine-grained evaluation of expertise than existing data sets do. We present and discuss baseline results for a language modelling and a topic-centric approach to expert search. We find that the topic-centric approach achieves the best results on domain-specific datasets. Presented at CSTA workshop, CIKM 2013, October 28, 2013]]> Tue, 29 Oct 2013 17:46:01 GMT /slideshow/benchmarking-27710760/27710760 ToineBogers@slideshare.net(ToineBogers) Benchmarking Domain-specific Expert Search using Workshop Program Committees ToineBogers Traditionally, relevance assessments for expert search have been gathered through self-assessment or based on the opinions of co-workers. We introduce three benchmark datasets for expert search that use conference workshops for relevance assessment. Our data sets cover entire research domains as opposed to single institutions. In addition, they provide a larger number of topic-person associations and allow a more objective and fine-grained evaluation of expertise than existing data sets do. We present and discuss baseline results for a language modelling and a topic-centric approach to expert search. We find that the topic-centric approach achieves the best results on domain-specific datasets. Presented at CSTA workshop, CIKM 2013, October 28, 2013 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/bordea2013-slides-131029174601-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Traditionally, relevance assessments for expert search have been gathered through self-assessment or based on the opinions of co-workers. We introduce three benchmark datasets for expert search that use conference workshops for relevance assessment. Our data sets cover entire research domains as opposed to single institutions. In addition, they provide a larger number of topic-person associations and allow a more objective and fine-grained evaluation of expertise than existing data sets do. We present and discuss baseline results for a language modelling and a topic-centric approach to expert search. We find that the topic-centric approach achieves the best results on domain-specific datasets. Presented at CSTA workshop, CIKM 2013, October 28, 2013

Benchmarking Domain-specific Expert Search using Workshop Program Committees from Toine Bogers

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