The document discusses Wordnet-Affect, an extension of Wordnet that adds affective information. It was built by manually adding affect labels and information to 1903 terms, then projecting this information to Wordnet synsets. The extension was done semi-automatically using Wordnet relations. Possible applications of Wordnet-Affect include sentiment analysis, verbal expressiveness for conversational agents, and computer-assisted creativity. In general, affective computing aims to enable computers to perceive and express emotion and can be applied in areas like adaptive entertainment and modifying environments.
3. Roadmap: We Are Here
Introduction to Affective Computing
Introduction to Wordnet-Affect
Process of Building Wordnet-Affect
Possible Applications
4. Affective Computing
Refers to processing of emotions
Enables computers to perceive and/or
express affect
Does NOT refer to:
Creating emotional computers
Introducing unreliability/unpredictability in computers
5. Need of Affective
Computing
Importance of emotion to humans
Vast wealth of information conveyed via
emotions [Sentic Modulation]
Body language
Facial expressions
Voice cues
Ability to enhance communication with
computers
6. Need of Affective
Computing
Importance of emotion to humans
Vast wealth of information conveyed via
emotions [Sentic Modulation]
Body language
Facial expressions
Voice cues
Ability to enhance communication with
computers
7. Need of Affective
Computing
Importance of emotion to humans
Vast wealth of information conveyed via
emotions [Sentic Modulation]
Body language
Facial expressions
Voice cues
Ability to enhance communication with
computers
8. Types of Affective
Computers
Cannot Express
Can Express
Cannot Perceive
Most computers today
Use of smileys, etc
Can Perceive
Teaching computers
Maximally user-friendly*
* Does NOT imply being driven by emotion
blue = Open Research Areas
9. Roadmap: We Are Here
Introduction to Affective Computing
Introduction to Wordnet-Affect
Process of Building Wordnet-Affect
Possible Applications
11. Need of Wordnet-Affect
Haphazard process of selecting emotion
words
Lack of emotion features
Need of distinguishing different senses of
the same word
12. Affect Information
A-label
Joy [joy, elation]
Love [love, worship]
Apprehension [trepidation, foreboding]
Sadness [misery, sorrow]
Surprise [surprise, astonishment]
Apathy [apathy, emotionlessness], etc.
POSR: Different POS but same emotion
[cheer, cheerful, cheerfulness, cheerfully]
17. Building Wordnet-Affect:
Core
Manual resource called Affect created with
1903 terms (not synsets)
Each term was given associated affect
information
Information was then projected from the
terms to Wordnet synsets
18. Building Wordnet-Affect:
Extension
Extension was performed using the following
Wordnet relations (similar to Sentiwordnet):
Direct antonymy
Similarity
Derived from
Pertains to
Attribute
Also see
19. Building Wordnet-Affect:
Extension
For other relations, similar expansion was
performed, but the synsets had to be filtered
manually.
Hypernym of cheer is attribute
Hyponym of murder is tyrannicide
20. Roadmap: We Are Here
Introduction to Affective Computing
Introduction to Wordnet-Affect
Process of Building Wordnet-Affect
Possible Applications
22. Applications of WordnetAffect
Computer-Assisted Creativity
Automated Personalized Advertisements
Verbal Expressivity for Conversational
Agents
Spoken Tutorials
Sentiment Analysis
Affective Text Sensing
23. Applications of WordnetAffect
Computer-Assisted Creativity
Automated Personalized Advertisements
Verbal Expressivity for Conversational
Agents
Spoken Tutorials
Sentiment Analysis
Affective Text Sensing
24. Applications of WordnetAffect
Computer-Assisted Creativity
Automated Personalized Advertisements
Verbal Expressivity for Conversational
Agents
Spoken Tutorials
Sentiment Analysis
Affective Text Sensing
25. Applications of Affective
Computing
Adaptive Entertainment
Automated DJing / Music concerts
Expressive E-mail
Avoiding misunderstandings over the internet by
encoding affect in written text
Film Processing & Viewing
Skip ahead to the interesting part
Environment Modifications
Temperature, Pressure, Color, etc
Aesthetic Entertainment
Capturing the subjectivity of art
26. Applications of Affective
Computing
Adaptive Entertainment
Automated DJing / Music concerts
Expressive E-mail
Avoiding misunderstandings over the internet by
encoding affect in written text
Film Processing & Viewing
Skip ahead to the interesting part
Environment Modifications
Temperature, Pressure, Color, etc
Aesthetic Entertainment
Capturing the subjectivity of art
27. Applications of Affective
Computing
Adaptive Entertainment
Automated DJing / Music concerts
Expressive E-mail
Avoiding misunderstandings over the internet by
encoding affect in written text
Film Processing & Viewing
Skip ahead to the interesting part
Environment Modifications
Temperature, Pressure, Color, etc
Aesthetic Entertainment
Capturing the subjectivity of art
28. Applications of Affective
Computing
Adaptive Entertainment
Automated DJing / Music concerts
Expressive E-mail
Avoiding misunderstandings over the internet by
encoding affect in written text
Film Processing & Viewing
Skip ahead to the interesting part
Environment Modifications
Temperature, Pressure, Color, etc
Aesthetic Entertainment
Capturing the subjectivity of art
29. Applications of Affective
Computing
Adaptive Entertainment
Automated DJing / Music concerts
Expressive E-mail
Avoiding misunderstandings over the internet by
encoding affect in written text
Film Processing & Viewing
Skip ahead to the interesting part
Environment Modifications
Temperature, Pressure, Color, etc
Aesthetic Entertainment
Capturing the subjectivity of art
32. Other References
Affective Computing by Picard, 1995; see also
I, Robot by Isaac Asimov
2001: A Space Odyssey by Arthur Clarke / Stanley Kubrick
The Affective Weight of Lexicon by Carlo Strapparava,
Alessandro Valitutti, Oliviero Stock, 2006
33. Further Plan
Lexicon-based Methods in Sentiment Analysis by Maite
Taboada, Julian Brooke, Milan Tofiloski, Kimberly Voll,
Manfred Stede, 2011 - DONE
Automatic Generation of Lexical Resources for Opinion
Mining by Andrea Esuli (PhD Thesis), 2008