1) The document outlines an experiment using an automatic affect annotation tool called ML-Ask to analyze emotive language in a large Japanese corpus.
2) ML-Ask uses dictionaries of emotive words and emotive morphemes to identify affective content and contextual valence shifters that can change the semantic orientation of evaluative words.
3) The experiment applies ML-Ask to analyze the 2channel forum, a large online discussion board, to evaluate the tool's ability to identify emotive language at scale.
The document describes CAO, a fully automatic emoticon analysis system. It defines emoticons and divides them into categories such as 1-line Western, 1-line Eastern, and multiline Eastern. The system was trained on a database of over 10,000 emoticons from online dictionaries, annotated with emotion types. CAO detects emoticons in text by identifying frequent character sequences and then analyzes detected emoticons by dividing them into components like eyes, mouth, and additional areas to determine the implied emotion.
Aristo Music provides a platform to create suitable musical atmospheres for any situation. It analyzes objective and subjective metadata to recommend music based on mood, activity, and context. The system is informed by research in musicology, psychology, and other fields to understand how music impacts humans.
This document discusses emotion detection in social media. It defines emotion as a reaction to important events that leads to changes in an organism. Emotion has five components: cognitive, neurophysiological, motivational/behavioral, motor expression, and subjective feeling. It discusses how emotions are detected in different media like facial expressions, gestures, voice, and text. Tools are presented that detect emotions in social media text to understand perceptions and attitudes. Detecting emotion helps analyze topics, competitors, and monitor discussions.
This document provides guidance for an assignment to create a literacy lesson that embeds comprehension and language development. The lesson must be based on an authentic text and include the following elements: objectives for both content and language, a rationale that references students' needs and professional literature, and a list of required materials. The objectives should link comprehension to an academic language structure beyond just vocabulary. The rationale must reflect knowledge of language and literacy development for the target grade level and student population.
Most descriptions of endangered languages focus on forms and structure: what are the vowels? How do you construct the passive? Imagine focusing on how linguistic resources are used emotionally — the creation of affective grammars. What sort of phenomena might we look for and what methods would we use? As a starting off point, I'll discuss my work on Shabo, an endangered isolate spoken in the coffee-growing mountains of Ethiopia.
http://linguistics.berkeley.edu/~fforum/2011-fall.php
The document describes CAO, a fully automatic emoticon analysis system. It defines emoticons and divides them into categories such as 1-line Western, 1-line Eastern, and multiline Eastern. The system was trained on a database of over 10,000 emoticons from online dictionaries, annotated with emotion types. CAO detects emoticons in text by identifying frequent character sequences and then analyzes detected emoticons by dividing them into components like eyes, mouth, and additional areas to determine the implied emotion.
Aristo Music provides a platform to create suitable musical atmospheres for any situation. It analyzes objective and subjective metadata to recommend music based on mood, activity, and context. The system is informed by research in musicology, psychology, and other fields to understand how music impacts humans.
This document discusses emotion detection in social media. It defines emotion as a reaction to important events that leads to changes in an organism. Emotion has five components: cognitive, neurophysiological, motivational/behavioral, motor expression, and subjective feeling. It discusses how emotions are detected in different media like facial expressions, gestures, voice, and text. Tools are presented that detect emotions in social media text to understand perceptions and attitudes. Detecting emotion helps analyze topics, competitors, and monitor discussions.
This document provides guidance for an assignment to create a literacy lesson that embeds comprehension and language development. The lesson must be based on an authentic text and include the following elements: objectives for both content and language, a rationale that references students' needs and professional literature, and a list of required materials. The objectives should link comprehension to an academic language structure beyond just vocabulary. The rationale must reflect knowledge of language and literacy development for the target grade level and student population.
Most descriptions of endangered languages focus on forms and structure: what are the vowels? How do you construct the passive? Imagine focusing on how linguistic resources are used emotionally — the creation of affective grammars. What sort of phenomena might we look for and what methods would we use? As a starting off point, I'll discuss my work on Shabo, an endangered isolate spoken in the coffee-growing mountains of Ethiopia.
http://linguistics.berkeley.edu/~fforum/2011-fall.php
Emotion Ontology and Affective NeuroscienceJanna Hastings
This document discusses annotating affective neuroscience data with the Emotion Ontology. It describes affective science and studies of emotional functioning and disorders using brain imaging. The Emotion Ontology aims to define emotion types and their characteristics. Studies of facial expression recognition, personal memory recall, and emotional sounds or films could be annotated with classes like visual perception of emotional stimuli or memory of emotional episodes. The ontology provides a framework for representing domain knowledge in a consistent way.
Invited talk at Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain, 2011/12/15.
This talk describes a computational framework for automatically predicting the emotion we perceive in music listening. Based on this computational framework, novel emotion-based music organization, browsing, and retrieval methods can be created to provide users an an intuitive, easy-to-use, and effective way for accessing music information.
This document outlines a music education project consisting of 7 points:
1) Defining oral expression, active listening, and emotional intelligence competencies.
2) Setting objectives for developing these competencies through activities.
3) Creating an evaluation rubric.
4) Conducting activities to improve oral expression, active listening, and managing emotions.
5) Collecting student opinions, which were positive about learning through music.
6) Providing a final evaluation of the project's impact in integrating and motivating students.
7) The final product was creating musical fairy tales and a website to share them.
Dr.S.Sundarabalu
Assistant Professor
Department of Linguistics
Bharathiar University,Coimbatore-46
Visiting Professor ,ICCR’s Tamil Chair
Institute of Oriental Studies,
Dept. of Indology Jagiellonian University,Krakow-Poland
sunder_balu@yahoo.co.in
India- 9715769995
Essay On Deforestation In Sanskrit LanguageJenny Price
1. Debit vouchers (SF 5515) are used to collect returned checks that were accepted in error by the disbursing office.
2. If a check is reported as issued with a value greater than zero but the payee is not entitled or it is returned, it cannot be voided and must be cancelled using cancellation procedures.
3. Debit vouchers are kept with the daily business records printed out by the Disbursing Office when electronic fund transfer payments are made using the Defense Department System (DDS).
Kow Kuroda's talk at Concept Workshop, Japan Psychological Association 2011Kow Kuroda
I was invited to Concepts Workshop of Japan Psychological Association, 2011, Japan and delivered a talk. This is the slides of what I talked about then.
This document discusses emotional intelligence and emotions-based testing. It introduces emotional intelligence (EQ) and its components: self-awareness, self-regulation, empathy, and social skills. The document provides examples of linking emotions like sadness, discontent, and joy to potential issues in testing approaches, test design, and test execution. It encourages investigating emotions and advocating for "EQ bugs" during testing. Small exercises are suggested to help participants reflect on their feelings and consider how to start with emotions-based testing.
The lesson plan summarizes a 2nd grade lesson on feelings taught in Romanian and English. The plan outlines activities to help students identify and express basic emotions like happiness, sadness, anger, fear, surprise and disgust in both languages. Students will learn vocabulary, discuss related emotions, recognize facial expressions, do roleplays and puzzles. The goal is for students to better understand and communicate their own feelings.
This document provides an introduction to literary devices through a game called "Guess the Gibberish". It defines common literary devices such as simile, metaphor, onomatopoeia, and personification. Examples are given for each device. An exercise then tests the reader to identify which literary device is being used in different sentences. The document concludes with a quick recap of the key devices and an exit ticket where readers are prompted to write their own sentences using the literary devices.
Mary Shelley uses powerful descriptive language to portray Frankenstein's emotional state at the moment of creating the creature as dangerous and obsessive. She emphasizes his "anxiety that almost amounted to agony" through alliteration, implying his actions could have dire consequences. This foreshadows the problems to come from Frankenstein overreaching his role and interfering with nature. The subtitle "The Modern Prometheus" further warns of the dangers of mankind thinking they can play God through science.
The Joze Jancar memorial lecture on Neurodevelopmental psychiatry given at the 2012 Annual residential conference of the Faculty of Intellectual Disability of the Royal College of Psychiatrists
Greene county etymology and morphology january 15branzburg
The workshop included the following activities:
- Discussing the origins of ancient Egyptian words and their meanings.
- Brainstorming possibilities for creating new "-ologies" and "-ologists" based on areas of expertise.
- Analyzing Latin and Greek word origins and their influence on the English language.
- Playing guessing games to learn the histories and meanings of words.
- Creating charts to show how words can change forms and meanings through prefixes, suffixes, and morphological transformations.
- Mapping networks of related words connected to common roots, prefixes, and suffixes.
NLP (Neuro-linguistic Programming) is an approach to communications, change, and performance that considers both the conscious and unconscious mind. It defines states as the combination of thoughts, emotions, and physical energy that determine one's mood. States can be either resourceful or unresourceful. People create their states based on how they perceive the world through their five senses, but this perception is altered by processes of deletion, distortion, and generalization of information before it reaches the conscious mind.
This document provides a self-instructional module on sound devices for English 6 students. It includes an introduction to sound devices like onomatopoeia, alliteration, assonance and consonance. It then has a pre-test for students to assess their existing knowledge. The document outlines the learning objectives for the module and what students will be able to do after completing it. It provides examples and explanations of different sound devices.
The study of word construction involves analyzing morphemes. There are two types of morphemes: free morphemes and bound morphemes. Free morphemes can stand alone as words, while bound morphemes need to be attached to other morphemes. The document then discusses several activities for students to complete involving identifying and analyzing prefixes, suffixes, and Latin and Greek roots of words.
Expressing and understanding dialogue act: Is it an explicit or an implicit process?
It must be implicit because:
- The age of acquisition
- Reaction time
Additional evidence
- People tend to give postdictive explanations that are not always correct for what they did.
The document discusses using the Myers-Briggs Type Indicator (MBTI) personality assessment tool along with the book "You: Being More Effective in Your MBTI Type" to help individuals better understand their personality type and develop themselves. It provides an overview of key concepts from the book, including type dynamics and the 8 mental processes. Understanding one's dominant and auxiliary functions, as well as tertiary and inferior functions, can help with personal and professional development when using the MBTI assessment results.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Emotion Ontology and Affective NeuroscienceJanna Hastings
This document discusses annotating affective neuroscience data with the Emotion Ontology. It describes affective science and studies of emotional functioning and disorders using brain imaging. The Emotion Ontology aims to define emotion types and their characteristics. Studies of facial expression recognition, personal memory recall, and emotional sounds or films could be annotated with classes like visual perception of emotional stimuli or memory of emotional episodes. The ontology provides a framework for representing domain knowledge in a consistent way.
Invited talk at Music Technology Group, Universitat Pompeu Fabra, Barcelona, Spain, 2011/12/15.
This talk describes a computational framework for automatically predicting the emotion we perceive in music listening. Based on this computational framework, novel emotion-based music organization, browsing, and retrieval methods can be created to provide users an an intuitive, easy-to-use, and effective way for accessing music information.
This document outlines a music education project consisting of 7 points:
1) Defining oral expression, active listening, and emotional intelligence competencies.
2) Setting objectives for developing these competencies through activities.
3) Creating an evaluation rubric.
4) Conducting activities to improve oral expression, active listening, and managing emotions.
5) Collecting student opinions, which were positive about learning through music.
6) Providing a final evaluation of the project's impact in integrating and motivating students.
7) The final product was creating musical fairy tales and a website to share them.
Dr.S.Sundarabalu
Assistant Professor
Department of Linguistics
Bharathiar University,Coimbatore-46
Visiting Professor ,ICCR’s Tamil Chair
Institute of Oriental Studies,
Dept. of Indology Jagiellonian University,Krakow-Poland
sunder_balu@yahoo.co.in
India- 9715769995
Essay On Deforestation In Sanskrit LanguageJenny Price
1. Debit vouchers (SF 5515) are used to collect returned checks that were accepted in error by the disbursing office.
2. If a check is reported as issued with a value greater than zero but the payee is not entitled or it is returned, it cannot be voided and must be cancelled using cancellation procedures.
3. Debit vouchers are kept with the daily business records printed out by the Disbursing Office when electronic fund transfer payments are made using the Defense Department System (DDS).
Kow Kuroda's talk at Concept Workshop, Japan Psychological Association 2011Kow Kuroda
I was invited to Concepts Workshop of Japan Psychological Association, 2011, Japan and delivered a talk. This is the slides of what I talked about then.
This document discusses emotional intelligence and emotions-based testing. It introduces emotional intelligence (EQ) and its components: self-awareness, self-regulation, empathy, and social skills. The document provides examples of linking emotions like sadness, discontent, and joy to potential issues in testing approaches, test design, and test execution. It encourages investigating emotions and advocating for "EQ bugs" during testing. Small exercises are suggested to help participants reflect on their feelings and consider how to start with emotions-based testing.
The lesson plan summarizes a 2nd grade lesson on feelings taught in Romanian and English. The plan outlines activities to help students identify and express basic emotions like happiness, sadness, anger, fear, surprise and disgust in both languages. Students will learn vocabulary, discuss related emotions, recognize facial expressions, do roleplays and puzzles. The goal is for students to better understand and communicate their own feelings.
This document provides an introduction to literary devices through a game called "Guess the Gibberish". It defines common literary devices such as simile, metaphor, onomatopoeia, and personification. Examples are given for each device. An exercise then tests the reader to identify which literary device is being used in different sentences. The document concludes with a quick recap of the key devices and an exit ticket where readers are prompted to write their own sentences using the literary devices.
Mary Shelley uses powerful descriptive language to portray Frankenstein's emotional state at the moment of creating the creature as dangerous and obsessive. She emphasizes his "anxiety that almost amounted to agony" through alliteration, implying his actions could have dire consequences. This foreshadows the problems to come from Frankenstein overreaching his role and interfering with nature. The subtitle "The Modern Prometheus" further warns of the dangers of mankind thinking they can play God through science.
The Joze Jancar memorial lecture on Neurodevelopmental psychiatry given at the 2012 Annual residential conference of the Faculty of Intellectual Disability of the Royal College of Psychiatrists
Greene county etymology and morphology january 15branzburg
The workshop included the following activities:
- Discussing the origins of ancient Egyptian words and their meanings.
- Brainstorming possibilities for creating new "-ologies" and "-ologists" based on areas of expertise.
- Analyzing Latin and Greek word origins and their influence on the English language.
- Playing guessing games to learn the histories and meanings of words.
- Creating charts to show how words can change forms and meanings through prefixes, suffixes, and morphological transformations.
- Mapping networks of related words connected to common roots, prefixes, and suffixes.
NLP (Neuro-linguistic Programming) is an approach to communications, change, and performance that considers both the conscious and unconscious mind. It defines states as the combination of thoughts, emotions, and physical energy that determine one's mood. States can be either resourceful or unresourceful. People create their states based on how they perceive the world through their five senses, but this perception is altered by processes of deletion, distortion, and generalization of information before it reaches the conscious mind.
This document provides a self-instructional module on sound devices for English 6 students. It includes an introduction to sound devices like onomatopoeia, alliteration, assonance and consonance. It then has a pre-test for students to assess their existing knowledge. The document outlines the learning objectives for the module and what students will be able to do after completing it. It provides examples and explanations of different sound devices.
The study of word construction involves analyzing morphemes. There are two types of morphemes: free morphemes and bound morphemes. Free morphemes can stand alone as words, while bound morphemes need to be attached to other morphemes. The document then discusses several activities for students to complete involving identifying and analyzing prefixes, suffixes, and Latin and Greek roots of words.
Expressing and understanding dialogue act: Is it an explicit or an implicit process?
It must be implicit because:
- The age of acquisition
- Reaction time
Additional evidence
- People tend to give postdictive explanations that are not always correct for what they did.
The document discusses using the Myers-Briggs Type Indicator (MBTI) personality assessment tool along with the book "You: Being More Effective in Your MBTI Type" to help individuals better understand their personality type and develop themselves. It provides an overview of key concepts from the book, including type dynamics and the 8 mental processes. Understanding one's dominant and auxiliary functions, as well as tertiary and inferior functions, can help with personal and professional development when using the MBTI assessment results.
Similar to Pacling 2009 ptaszynski_presentation (20)
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
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1. Michal Ptaszynski
Pawel Dybala, Rafal Rzepka, Kenji Araki
AFFECTING CORPORA:
EXPERIMENTS WITH AUTOMATIC
AFFECT ANNOTATION SYSTEM
– A Case Study of the 2channel Forum –
2. Presentation Outline
Introduction
Specificities of the Japanese language
ML-Ask – Automatic affect annotation tool
Contextual Valence Shifters
Evaluation of ML-Ask
Experiment on a large corpus
Results
Conclusions
Future Works
3. Introduction
Some problems with today affect analysis systems
(for Japanese)
① No standards for emotion type classification
② Simplified classification (+/- , happiness/sadness)
③ How to tell if the utterance is emotive?
④ No evaluations on large corpora
① compare:
Endo, D., Saito, S. and Yamamoto, K. Kakariuke kankei wo riyo shita kanjoseikihyogen no chushutsu.(Extracting expressions evoking emotions using
dependency structure), Proceedings of The Twelve Annual Meeting of The Association for Natural Language Processing. 2006
Tsuchiya, Seiji, Yoshimura, Eriko, Watabe, Hirokazu and Kawaoka, Tsukasa. The Method of the Emotion Judgment Based on an Association
Mechanism.
Journal of Natural Language Processing, Vol.14, No.3, The Association for Natural Language Processing. 2007
Ryoko Tokuhisa, Kentaro Inui, Yuji Matsumoto. Emotion Classification Using Massive Examples Extracted from the Web, In Proc. of Coling
2008,pp.881-888,2008.
②
Peter D. Turney. 2002. Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews. In Proceedings of
ACL’02, pp. 417-424
Jorge Teixeira, Vasco Vinhas, Eugenio Oliveira and Luis Reis. A New Approach to Emotion Assessment Based on Biometric Data. In Proceedings of
WI-IAT’08, pages 459-500, 2008.
③
Ryoko Tokuhisa, Kentaro Inui, Yuji Matsumoto. Emotion Classification Using Massive Examples Extracted from the Web, In Proc. of Coling
2008,pp.881-888,2008.
④
Junko Minato, David B. Bracewell, Fuji Ren and Shingo Kuroiwa. 2006. Statistical Analysis of a Japanese Emotion Corpus for Natural Language
Processing. LNCS 4114.
4. Specificities of the Japanese language
Agglutinative language
•Morpheme : the smallest linguistic
unit with semantic meaning
•Sentences are formed by joining
morphemes together
•Syntax and semantics are closer
than in, e.g. English
5. ML-Ask – Automatic affect annotation tool
Usual approach to affect analysis:
A database of emotive words *
Processing (Matching input with databases,
machine learning, Web mining, word statistics, etc.)
Example: “John is a nice person.”
Emotive expression: “nice”
emotion: liking, fondness
…but that’s just a declarative sentence.
In a real conversation:
“Oh, but John is such a nice person !”
*) For example: WordNet Affect in English: Strapparava, C., Valitutti, A.: An Affective Extension of WordNet, Proceedings of LREC’04, pp.1083-1086.(2004)
In Japanese: manually build: Seiji Tsuchiya, Eriko Yoshimura, Hirokazu Watabe and Tsukasa Kawaoka, Proposal of Method to Judge Speaker's Emotion Based on
Association Mechanism, KES2007, Vol.1, pp.847-857, 2007; enriched with Web minig: Ryoko Tokuhisa, Kentaro Inui, and Yuji Matsumoto. Emotion classification using
massive examples extracted from the Web. In Proceedings of the 22nd International Conference on Computational Linguistics (COLING-2008), pp881-888, Aug. 2008
6. ML-Ask – Automatic affect annotation tool
Our approach to affect analysis:
In language there are:
1. Emotive/evaluative expressions*
2. Emotiveness indicators. “Emotemes” – Japanese
emotive morphemes**
“Oh, but John is such a nice person !”
“Oh, but John is such a rude person !”
*) A. Nakamura, Kanjō hyōgen jiten (Dictionary of Emotive Expressions), Tokyodo Publishing, Tokyo (1993)
**) M. Ptaszyński, Moeru gengo - Intānetto kei-jiban no ue no nihongo kaiwa ni okeru kanjōhyōgen no kōzō to kigōrontekikinō no bunseki – “2channeru„ denshikeijiban o rei toshite –(Boisterous
language. Analysis of structures and semiotic functions of emotive expressions in conversation on Japanese Internet bulletin board forum - 2channel -), UAM, Poznań (2006)
Michal Ptaszynski, Pawel Dybala, Rafal Rzepka and Kenji Araki. Effective Analysis of Emotiveness in Utterances based on Features of Lexical and Non-Lexical Layer of Speech. In Proceedings
of NLP2008, pp 171-174, 2008.
Michal Ptaszynski, Pawel Dybala, Rafal Rzepka and Kenji Araki. Affecting Corpora:Experiments with Automatic Affect Annotation System - A Case Study of the 2channel
Forum -, The Conference of the Pacific Association for Computational Linguistics (PACLING-09), September 1-4, 2009, Hokkaido University, Sapporo, Japan
8. ML-Ask – Automatic affect annotation tool
コンピュータは面白いですね!
Konpyuuta wa omoshiroi desu ne!
Oh, computers are so interesting!
Found emotemes: ne, !
(for English: oh, so-)
input Utterance is: emotive
Found emotive
expressions: omoshiroi
(interesting)
Conveyed emotion types:
joy
9. ML-Ask – Automatic affect annotation tool
Problematic inputs:
あんまり面白くなかったな…
Anmari omoshiroku nakatta na… Found emotemes: na, ...
(for English: oh, ...)
Oh, it wasn’t that interesting... Utterance is: emotive
Found emotive
expressions: omoshiroi
(interesting)
Conveyed emotion types:
joy
10. ML-Ask – Automatic affect annotation tool
Problematic inputs:
あんまり面白くなかったな…
Anmari omoshiroku nakatta na… Found emotemes: na, ...
(for English: oh, ...)
Oh, it wasn’t that interesting... Utterance is: emotive
Found emotive
expressions: omoshiroi
(interesting)
Conveyed emotion types:
joy
11. Contextual Valence Shifters
Polanyi, L. and Zaenen, A. (2004) ‘Contextual
Valence Shifters’, AAAI Spring Symposium on
Exploring Attitude and Affect in Text: Theories
and Applications.
(Published later by Springer:Computing
Attitude and Affect in Text: Theory and
Applications)
12. Contextual Valence Shifters
Definition:
The group of words and phrases, which change the
semantic orientation (valence polarity) of an evaluative
word.
negations: not- , never-, etc., in Japanese: amari -nai
(not quite-), mattaku -nai (not at all-), or sukoshi mo -nai
(not even a bit-).
intensifiers: very- , deeply- , etc., in Japanese: totemo-
(very much-), sugoku- (-a lot), or kiwamete- (extremely).
13. Contextual Valence Shifters
Examples:
John is clever vs. John is not clever.
clever +1 combined with not ->not clever -1
John is successful at tennis vs. John is never
successful at tennis.
successful +1 combined with not -> not successful -1
Each of them is successful vs. None of them is
successful.
Polanyi, L. and Zaenen, A. (2004)
16. Contextual Valence Shifters
2-dimensional model of affect.
“All emotions can be described in
a space of two-dimensions: active
activated
valence polarity
(positive / negative) and do / ikari (anger)
fu / kowagari (fear) ki / yorokobi (joy, delight)
activation (active / passive).” kou / takaburi (excitement) kou / suki (liking, fondness)
en / iya (dislike, detestation) kou / takaburi (excitement)
kyou / odoroki (surprise, amazement) kyou / odoroki (surprise, amazement)
chi / haji (shame, shyness, bashfulness) chi / haji (shame, shyness, bashfulness)
negative positive
Nakamura’s emotion
en / iya (dislike, detestation) kou / suki (liking, fondness)
types mapped on
ai / aware (sorrow, sadness) ki / yorokobi (joy, delight)
Russell’s model
an / yasuragi (relief)
(all possibilities)
deactivated
passive
H. Schlosberg. “The description of facial expressions in terms of two dimensions.” Journal of Experimental Psychology, 44:229-237. 1952.
James A. Russell. “A circumplex model of affect.” Journal of Personality and Social Psychology, 39(6):1161-1178. 1980.
17. Contextual Valence Shifters
2-dimensional model of affect.
“All emotions can be described in
a space of two-dimensions:
valence polarity active
(positive / negative) and
activation (active / passive).
Assumption:
CVS negation changes
both valence and
activation parameters
passive
H. Schlosberg. “The description of facial expressions in terms of two dimensions.” Journal of Experimental Psychology, 44:229-237. 1952.
James A. Russell. “A circumplex model of affect.” Journal of Personality and Social Psychology, 39(6):1161-1178. 1980.
19. Evaluation of ML-Ask
Emotive / not-emotive
questionnaire (layperson): 80 sentences
(40 emotive, 40 non-emotive)
ML-Ask annotated correctly 72 from 80 utterances
(90% of agreements)
The system‘s agreement with annotators was indicated
as very strong (kappa=.8).
Error description:
In 2 cases the system wrongly annotated utterances as
"emotive“
in 6 cases it was the opposite.
20. Evaluation of ML-Ask
Emotive / not-emotive
questionnaire (layperson): 80 sentences
(40 emotive, 40 non-emotive)
ML-Ask annotated correctly 72 from 80 utterances
(90%)
The system‘s agreement with annotators was indicated
as very high (kappa=.8).
Error description:
In 2 cases the system wrongly annotated utterances as
"emotive“
in 6 cases it was the opposite.
21. Evaluation of ML-Ask
Emotion types
Emotive expressions extracted from 9 out of 40 emotive
sentences (Recall = 0.225)
All extracted correctly (Precision = 1.00)
Balanced F-score = 0.367
22. Evaluation of ML-Ask
Emotion types
Emotive expressions extracted from 9 out of 40 emotive
sentences (Recall = 0.225)
All extracted correctly (Precision = 1.00)
Balanced F-score = 0.367
Why so
low?
23. Evaluation of ML-Ask
Emotion types
Emotive expressions extracted from 9 out of 40 emotive
sentences (Recall = 0.225)
All extracted correctly (Precision = 1.00)
Balanced F-score = 0.367
Why so
low?
Precision = 1.00, so Nakamura’s dictionary is OK,
but:
1.Nakamura’s lexicon is out-of-date (only ~2100 expressions
gathered till year 1993)
2.People use ambiguous emotive utterances, where emphasis is
based on context
24. Experiment on a large corpus
2channel BBS forum (http://www.2ch.net/)
Special feature: lots of expressive contents
ROBUST!!!
For 2003.10
number of
comments on
2channel was
TWO TIMES as
on asahi.com !
Nakazawa Shin’ichi (2004) “2channeru
koushiki gaido 2004”, Tokyo, Koamagajin
25. Experiment on a large corpus
Processing all is… difficult
Lets take only a part of it:
Densha otoko 電車男 (Train man)*
177,553 characters
in 1,840 utterances
divided into 6 parts/chapters.
* Hitori Nakano. 2005. Densha otoko [Train man]. Tokyo, Shinchosha.
26. Experiment on a large corpus
Processing all is… difficult
Lets take only a part of it:
Densha otoko 電車男 (Train man)*
177,553 characters
in 1,840 utterances
divided into 6 parts/chapters.
…Its annotated!
Manual affect annotation (Ptaszynski 2006)**
2 annotators
Only utterances containing emotive expressions
(ambiguously emotive utterances appeared too frequently)
* Hitori Nakano. 2005. Densha otoko [Train man]. Tokyo, Shinchosha.
** Michal Ptaszynski. 2006. Boisterous language. Analysis of structures and semiotic functions of emotive expressions in conversation on Japanese Internet bulletin board forum
'2channel', M.A. Dissertation, UAM, Poznan.
27. Experiment on a large corpus
Processing all is… difficult
Lets take only a part of it:
Densha otoko 電車男 (Train man)*
177,553 characters
in 1,840 utterances
divided into 6 parts/chapters.
…Its annotated!
Manual affect annotation (Ptaszynski 2006)**
2 annotators
Only utterances containing emotive expressions
(ambiguously emotive utterances appeared too frequently)
We annotated the corpus using ML-Ask and compared the results.
* Hitori Nakano. 2005. Densha otoko [Train man]. Tokyo, Shinchosha.
** Michal Ptaszynski. 2006. Boisterous language. Analysis of structures and semiotic functions of emotive expressions in conversation on Japanese Internet bulletin board forum
'2channel', M.A. Dissertation, UAM, Poznan.
28. Results
There were 1560 emotive utterances
(81% of all corpus)
29. Results
Emotive utterances containing specified emotive expressions:
19% to 25% of the corpus contained emotive expressions =
its 40% to 75% (Average of 58%) of the human level
annotations, + similar tendency
Results were very statistically significant, P value = .0052
32. Results
Emotion type annotation tendencies
Similar:
8/10 types (joy, anger, gloom, fear, shame/shyness,
fondness, relief and surprise)
Problematic: 2/10 types (dislike, excitement)
To express these two emotions in
particular, 2channel users mostly
use slang (ASCII, unusual emoticons,
etc. – difficult to process
mechanically!).
33. Excitement
Results
Emotion type annotation tendencies
Similar:
8/10 types (joy, anger, gloom, fear, shame/shyness,
fondness, relief and surprise)
Problematic: 2/10 types (dislike, excitement)
To express these two emotions in
particular, 2channel users mostly
use slang (ASCII, unusual emoticons,
etc. – difficult to process
mechanically!).
Dislike
34. Results
Except of these two emotion types:
90% of agreements with human annotators
with a good strength of agreement coefficient
(Kappa = .681)
Results were very statistically significant
(P value = .0035).
35. Conclusions
We presented ML-Ask, a system for automatic
annotation of corpora with emotive information.
Emotive / non-emotive – high accuracy
Emotion types – high precision, low recall
We performed an annotation experiment on a large
corpus (discussions from a popular Japanese forum
2channel).
Manual annotation of the corpus was the gold standard
ML-Ask was successful in providing information on
tendencies of emotive utterances in conversations.
36. Future Work
Updating the emotive expressions lexicon
Statistically disambiguate emotive affiliations of
emotemes (e.g. an exclamation mark would be used
with ”excitement”, rather than with ”gloom”)
Experiments including large scale annotations of
other natural dialogue corpora
Find out about the functions emotive utterances play
in different contexts and conversation environments.
37. Thank you for your attention!
Michal PTASZYNSKI
Language Media Laboratory
Graduate School of Information Science and Technology
Hokkaido University
Address: Kita-ku, Kita 14 Nishi 9, 060-0814 Sapporo, Japan
E-mail: ptaszynski@media.eng.hokudai.ac.jp