�ݺ�ߣshows by User: MatteoManca

�ݺ�ߣshows by User: MatteoManca / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: MatteoManca / Mon, 20 Nov 2017 22:42:40 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: MatteoManca Urban Patterns and Citizen Participation: Geographical Data Analysis of Decidim Barcelona /slideshow/urban-patterns-and-citizen-participation-geographical-data-analysis-of-decidim-barcelona/82412131 decidim-171120224240
European Symposium Series on Societal Challenges in Computational Social Science]]>
European Symposium Series on Societal Challenges in Computational Social Science]]> Mon, 20 Nov 2017 22:42:40 GMT /slideshow/urban-patterns-and-citizen-participation-geographical-data-analysis-of-decidim-barcelona/82412131 MatteoManca@slideshare.net(MatteoManca) Urban Patterns and Citizen Participation: Geographical Data Analysis of Decidim Barcelona MatteoManca European Symposium Series on Societal Challenges in Computational Social Science <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/decidim-171120224240-thumbnail.jpg?width=120&height=120&fit=bounds" /> European Symposium Series on Societal Challenges in Computational Social Science

Urban Patterns and Citizen Participation: Geographical Data Analysis of Decidim Barcelona from Matteo Manca

]]> 160 2 https://cdn.slidesharecdn.com/ss_thumbnails/decidim-171120224240-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 Gender inequalities in political participation: a study of the 2017 UK general elections on Twitter /slideshow/gender-inequalities-in-political-participation-a-study-of-the-2017-uk-general-elections-on-twitter/82412032 slidesgenderuk-171120224051
European Symposium Series on Societal Challenges in Computational Social Science]]>
European Symposium Series on Societal Challenges in Computational Social Science]]> Mon, 20 Nov 2017 22:40:51 GMT /slideshow/gender-inequalities-in-political-participation-a-study-of-the-2017-uk-general-elections-on-twitter/82412032 MatteoManca@slideshare.net(MatteoManca) Gender inequalities in political participation: a study of the 2017 UK general elections on Twitter MatteoManca European Symposium Series on Societal Challenges in Computational Social Science <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/slidesgenderuk-171120224051-thumbnail.jpg?width=120&height=120&fit=bounds" /> European Symposium Series on Societal Challenges in Computational Social Science

Gender inequalities in political participation: a study of the 2017 UK general elections on Twitter from Matteo Manca

]]> 211 5 https://cdn.slidesharecdn.com/ss_thumbnails/slidesgenderuk-171120224051-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 From Social Science to Computational Social Science: Is Web Data the Key to a More Effective Analysis? /slideshow/from-social-science-to-computational-social-science-is-web-data-the-key-to-a-more-effective-analysis/82410578 digbehavworkshop-171120221252
European Symposium Series on Societal Challenges in Computational Social Science]]>
European Symposium Series on Societal Challenges in Computational Social Science]]> Mon, 20 Nov 2017 22:12:51 GMT /slideshow/from-social-science-to-computational-social-science-is-web-data-the-key-to-a-more-effective-analysis/82410578 MatteoManca@slideshare.net(MatteoManca) From Social Science to Computational Social Science: Is Web Data the Key to a More Effective Analysis? MatteoManca European Symposium Series on Societal Challenges in Computational Social Science <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/digbehavworkshop-171120221252-thumbnail.jpg?width=120&height=120&fit=bounds" /> European Symposium Series on Societal Challenges in Computational Social Science

From Social Science to Computational Social Science: Is Web Data the Key to a More Effective Analysis? from Matteo Manca

]]> 126 3 https://cdn.slidesharecdn.com/ss_thumbnails/digbehavworkshop-171120221252-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 The dynamics of a social convention /slideshow/the-dynamics-of-a-social-convention-78492465/78492465 cs2school-170729084040-170802120626
Summer School on Methods for Computational Social Science - Group Project]]>
Summer School on Methods for Computational Social Science - Group Project]]> Wed, 02 Aug 2017 12:06:25 GMT /slideshow/the-dynamics-of-a-social-convention-78492465/78492465 MatteoManca@slideshare.net(MatteoManca) The dynamics of a social convention MatteoManca Summer School on Methods for Computational Social Science - Group Project <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/cs2school-170729084040-170802120626-thumbnail.jpg?width=120&height=120&fit=bounds" /> Summer School on Methods for Computational Social Science - Group Project

The dynamics of a social convention from Matteo Manca

]]> 119 2 https://cdn.slidesharecdn.com/ss_thumbnails/cs2school-170729084040-170802120626-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 Introduction to data pre-processing and cleaning /slideshow/introduction-to-data-preprocessing-and-cleaning-60693383/60693383 datacleanok-160409140410
Brief Introduction to data pre-processing and cleaning ]]>
Brief Introduction to data pre-processing and cleaning ]]> Sat, 09 Apr 2016 14:04:10 GMT /slideshow/introduction-to-data-preprocessing-and-cleaning-60693383/60693383 MatteoManca@slideshare.net(MatteoManca) Introduction to data pre-processing and cleaning MatteoManca Brief Introduction to data pre-processing and cleaning <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/datacleanok-160409140410-thumbnail.jpg?width=120&height=120&fit=bounds" /> Brief Introduction to data pre-processing and cleaning

Introduction to data pre-processing and cleaning from Matteo Manca

]]> 1790 5 https://cdn.slidesharecdn.com/ss_thumbnails/datacleanok-160409140410-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 Behavioral Data Mining to Produce Novel and Serendipitous Friend Recommendations in a Social Bookmarking System /slideshow/behavioral-data-mining-to-produce-novel-and-serendipitous-friend-recommendaons-in-a-social-bookmarking-system/54853085 eurecatfrpub-151107135820-lva1-app6891
Eurecat Talk - October 21, 2015: In the last few years, social media systems have experienced a fast growth. The amount of content shared in these systems increases fast, leading users to face the well known “interaction overload” problem, i.e., they are overwhelmed by content, so it becomes difficult to come across interesting items. To overcome this problem, social recommender systems have been recently designed and developed in order to filter content and recommend to users only interesting items. This type of filtering is usually affected by the “over-specialization” problem, which is related to recommendations that are too similar to the items already considered by the users. This paper proposes a friend recommender system that operates in the social bookmarking application domain and is based on behavioral data mining, i.e., on the exploitation of the users activity in a social bookmarking system. Experimental results show how this type of mining is able to produce accurate friend recommendations, allowing users to get to know bookmarked resources that are both novel and serendipitous. Using this approach, the impact of the “interaction overload” and the “over-specialization” problems is strongly reduced.]]>
Eurecat Talk - October 21, 2015: In the last few years, social media systems have experienced a fast growth. The amount of content shared in these systems increases fast, leading users to face the well known “interaction overload” problem, i.e., they are overwhelmed by content, so it becomes difficult to come across interesting items. To overcome this problem, social recommender systems have been recently designed and developed in order to filter content and recommend to users only interesting items. This type of filtering is usually affected by the “over-specialization” problem, which is related to recommendations that are too similar to the items already considered by the users. This paper proposes a friend recommender system that operates in the social bookmarking application domain and is based on behavioral data mining, i.e., on the exploitation of the users activity in a social bookmarking system. Experimental results show how this type of mining is able to produce accurate friend recommendations, allowing users to get to know bookmarked resources that are both novel and serendipitous. Using this approach, the impact of the “interaction overload” and the “over-specialization” problems is strongly reduced.]]> Sat, 07 Nov 2015 13:58:20 GMT /slideshow/behavioral-data-mining-to-produce-novel-and-serendipitous-friend-recommendaons-in-a-social-bookmarking-system/54853085 MatteoManca@slideshare.net(MatteoManca) Behavioral Data Mining to Produce Novel and Serendipitous Friend Recommendations in a Social Bookmarking System MatteoManca Eurecat Talk - October 21, 2015: In the last few years, social media systems have experienced a fast growth. The amount of content shared in these systems increases fast, leading users to face the well known “interaction overload” problem, i.e., they are overwhelmed by content, so it becomes difficult to come across interesting items. To overcome this problem, social recommender systems have been recently designed and developed in order to filter content and recommend to users only interesting items. This type of filtering is usually affected by the “over-specialization” problem, which is related to recommendations that are too similar to the items already considered by the users. This paper proposes a friend recommender system that operates in the social bookmarking application domain and is based on behavioral data mining, i.e., on the exploitation of the users activity in a social bookmarking system. Experimental results show how this type of mining is able to produce accurate friend recommendations, allowing users to get to know bookmarked resources that are both novel and serendipitous. Using this approach, the impact of the “interaction overload” and the “over-specialization” problems is strongly reduced. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/eurecatfrpub-151107135820-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds" /> Eurecat Talk - October 21, 2015: In the last few years, social media systems have experienced a fast growth. The amount of content shared in these systems increases fast, leading users to face the well known “interaction overload” problem, i.e., they are overwhelmed by content, so it becomes difficult to come across interesting items. To overcome this problem, social recommender systems have been recently designed and developed in order to filter content and recommend to users only interesting items. This type of filtering is usually affected by the “over-specialization” problem, which is related to recommendations that are too similar to the items already considered by the users. This paper proposes a friend recommender system that operates in the social bookmarking application domain and is based on behavioral data mining, i.e., on the exploitation of the users activity in a social bookmarking system. Experimental results show how this type of mining is able to produce accurate friend recommendations, allowing users to get to know bookmarked resources that are both novel and serendipitous. Using this approach, the impact of the “interaction overload” and the “over-specialization” problems is strongly reduced.

Behavioral Data Mining to Produce Novel and Serendipitous Friend Recommendations in a Social Bookmarking System from Matteo Manca

]]> 2955 6 https://cdn.slidesharecdn.com/ss_thumbnails/eurecatfrpub-151107135820-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 https://cdn.slidesharecdn.com/profile-photo-MatteoManca-48x48.jpg?cb=1706191268 I'm Data Scientist in the Digital Humanities research group at Eurecat, which I joined in September 2015; my main research activities are related to social media mining, social networks analysis and computational social science. Currently my efforts are focused on applying computational methods to digital trace data in order to gain knowledge about human behaviour and social phenomena. In 2014 I earned my PhD in computer science from the University of Cagliari with a thesis focused on the study and implementation of social recommendation approaches for the social media domain. In 2009, I got my master degree in computer science from the same university. Before joining Eurecat, I had worke... https://mattemanca.wordpress.com https://cdn.slidesharecdn.com/ss_thumbnails/decidim-171120224240-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/urban-patterns-and-citizen-participation-geographical-data-analysis-of-decidim-barcelona/82412131 Urban Patterns and Cit... https://cdn.slidesharecdn.com/ss_thumbnails/slidesgenderuk-171120224051-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/gender-inequalities-in-political-participation-a-study-of-the-2017-uk-general-elections-on-twitter/82412032 Gender inequalities in... https://cdn.slidesharecdn.com/ss_thumbnails/digbehavworkshop-171120221252-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/from-social-science-to-computational-social-science-is-web-data-the-key-to-a-more-effective-analysis/82410578 From Social Science to...