Emotional Tweets
Joint Conference on Lexical and Computational SemanticsPublished 7 June 2012
Saif M. Mohammad
Citations299
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
This paper describes how a Twitter emotion corpus is created from Twitter posts using emotion-word hashtags, and extracts a word-emotion association lexicon that leads to significantly better results than the manually crafted WordNet Affect lexicon in an emotion classification task.
Abstract
Detecting emotions in microblogs and social media posts has applications for industry, health, and security. However, there exists no microblog corpus with instances labeled for emotions for developing supervised systems. In this paper, we describe how we created such a corpus from Twitter posts using emotion-word hashtags. We conduct experiments to show that the self-labeled hashtag annotations are consistent and match with the annotations of trained judges. We also show how the Twitter emotion corpus can be used to improve emotion classification accuracy in a different domain. Finally, we extract a word-emotion association lexicon from this Twitter corpus, and show that it leads to significantly better results than the manually crafted WordNet Affect lexicon in an emotion classification task.
Keywords
Computer Science
ACM SIGKDD Explorations NewsletterThe WEKA data mining software
17,849 Citations2009Mark Hall, Eibe Frank +4 more
This paper provides an introduction to the WEKA workbench, reviews the history of the project, and, in light of the recent 3.6 stable release, briefly discusses what has been added since the last stable version (Weka 3.4) released in 2003.
Cognition & EmotionAn argument for basic emotions
9,365 Citations1992Paul Ekman
This work has shown that not only the intensity of an emotion but also its direction may vary greatly both in the amygdala and in the brain during the course of emotion regulation.
Proceedings of the International AAAI Conference on Web and Social MediaPredicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment
2,681 Citations2010Andranik Tumasjan, Timm O. Sprenger +2 more
It is found that the mere number of messages mentioning a party reflects the election result, and joint mentions of two parties are in line with real world political ties and coalitions.
Computational IntelligenceCROWDSOURCING A WORD–EMOTION ASSOCIATION LEXICON
2,584 Citations2012Saif M. Mohammad, Peter D. Turney
It is shown how the combined strength and wisdom of the crowds can be used to generate a large, high‐quality, word–emotion and word–polarity association lexicon quickly and inexpensively.
Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter
2,035 Citations2010danah boyd, Su Golder +1 more
This paper examines the practice of retweeting as a way by which participants can be "in a conversation" and highlights how authorship, attribution, and communicative fidelity are negotiated in diverse ways.
ArXiv.orgFrustratingly Easy Domain Adaptation
1,395 Citations2009Hal Daumé
This work describes an approach to domain adaptation that is appropriate exactly in the case when one has enough “target” data to do slightly better than just using only “source’ data.
Emotions from text
785 Citations2005Cecilia Ovesdotter Alm, Dan Roth +1 more
This paper explores the text-based emotion prediction problem empirically, using supervised machine learning with the SNoW learning architecture to classify the emotional affinity of sentences in the narrative domain of children's fairy tales, for subsequent usage in appropriate expressive rendering of text-to-speech synthesis.
Identifying Sarcasm in Twitter: A Closer Look
632 Citations2011Roberto González‐Ibáñez, Smaranda Muresan +1 more
This work reports on a method for constructing a corpus of sarcastic Twitter messages in which determination of the sarcasm of each message has been made by its author and uses this reliable corpus to compare sarcastic utterances in Twitter to utterances that express positive or negative attitudes without sarcasm.
FigshareA Latent Variable Model for Geographic Lexical Variation
607 Citations2018Jacob Eisenstein, Brendan O’Connor +2 more
A multi-level generative model that reasons jointly about latent topics and geographical regions is presented, which recovers coherent topics and their regional variants, while identifying geographic areas of linguistic consistency.
SemEval-2007 task 14
599 Citations2007Carlo Strapparava, Rada Mihalcea
The data set used in the evaluation and the results obtained by the participating systems are described, meant as an exploration of the connection between emotions and lexical semantics.
A model of textual affect sensing using real-world knowledge
531 Citations2003Hugo Liu, Henry Lieberman +1 more
This paper demonstrates a new approach, using large-scale real-world knowledge about the inherent affective nature of everyday situations to classify sentences into "basic" emotion categories, and suggests that the approach is robust enough to enable plausible affective text user interfaces.
Lecture notes in computer scienceIdentifying Expressions of Emotion in Text
449 Citations2007Saima Aman, Stan Śzpakowicz
An emotion annotation task of identifying emotion category, emotion intensity and the words/phrases that indicate emotion in text is described and results of an annotation agreement study on a corpus of blog posts are presented.
arXiv (Cornell University)Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena
318 Citations2009Johan Bollen, Alberto Pepe +1 more
PRESENCE Virtual and Augmented RealitySpatial Presence and Emotions during Video Game Playing: Does It Matter with Whom You Play?
312 Citations2006Niklas Ravaja, Timo Saari +4 more
Playing against another human elicited higher spatial presence, engagement, anticipated threat, post-game challenge appraisals, and physiological arousal, as well as more positively valenced emotional responses, compared to playing against a stranger.
Modeling emotions and other motivations in synthetic agents
275 Citations1997Juan D. Velásquez
Cathexis is a distributed, computational model which offers an alternative approach to model the dynamic nature of different affective phenomena, such as emotions, moods and temperaments, and provides a flexible way of modeling their influence on the behavior of synthetic autonomous agents.
Using Analytic QP and Sparseness to Speed Training of Support Vector Machines
266 Citations1998John Platt
An algorithm for training SVMs: Sequential Minimal Optimization, or SMO, which breaks the large QP problem into a series of smallest possible QP problems which are analytically solvable and does not require a numerical QP library.
A Corpus-based Approach to Finding Happiness
174 Citations2006Rada Mihalcea, Hugo Liu
This paper employs ‘linguistic ethnography’ to seek out where happiness lies in everyday lives by considering a corpus of blogposts from the LiveJournal community annotated with happy and sad moods, and concludes by offering a corpus-inspired livable recipe for happiness.
arXiv (Cornell University)Tracking Sentiment in Mail: How Genders Differ on Emotional Axes
172 Citations2013Saif M. Mohammad, T.Y. Yang +1 more
Decision Support SystemsFrom once upon a time to happily ever after: Tracking emotions in mail and books
157 Citations2012Saif M. Mohammad
It is shown how sentiment analysis can be used in tandem with effective visualizations to quantify and track emotions in mail and books and that fairy tales have more extreme emotion densities than novels.
Lecture notes in computer scienceUsing a Heterogeneous Dataset for Emotion Analysis in Text
150 Citations2011Soumaya Chaffar, Diana Inkpen
This paper adopts a supervised machine learning approach to recognize six basic emotions using a heterogeneous emotion-annotated dataset which combines news headlines, fairy tales and blogs.
Proceedings of the International AAAI Conference on Web and Social MediaCompositionality Principle in Recognition of Fine-Grained Emotions from Text
116 Citations2009Alena Neviarouskaya, Helmut Prendinger +1 more
The evaluation of the Affect Analysis Model algorithm showed promising results regarding its capability to accurately recognize affective information in text from an existing corpus of personal blog posts.
Lecture notes in computer scienceEmotional Sequencing and Development in Fairy Tales
96 Citations2005Cecilia Ovesdotter Alm, Richard Sproat
The study is motivated by the need for exploring features for text-based emotion prediction at the sentence-level, for use in expressive text-to-speech synthesis of children’s stories.
Lecture notes in computer scienceEmotion Estimation and Reasoning Based on Affective Textual Interaction
94 Citations2005Chunling Ma, Helmut Prendinger +1 more
The emotion estimation module is applied to a chat system, where avatars associated with chat partners act out the assessed emotions of messages through multiple modalities, including synthetic speech and associated affective gestures.
Text-to-Emotion Engine for Real Time Internet Communication
81 Citations2014Zhe Xu, Anthony C. Boucouvalas
The latest version of an emotion extraction engine used for real time Internet text communication is presented and can analyse input text from a chat environment, extract the emotion being communicated, and deliver the parameters necessary to invoke an appropriate expressive image on screen to the communicating user display.
North American Chapter of the Association for Computational LinguisticsPortable Features for Classifying Emotional Text
76 Citations2012Saif M. Mohammad
It is shown that even in supervised settings, an affect lexicon can provide significant gains and that while ngram features tend to be accurate, they are often unsuitable for use in new domains.
Identifying Emotions, Intentions, and Attitudes in Text Using a Game with a Purpose
35 Citations2010Lisa Pearl, Mark Steyvers
This work describes a methodology for creating databases of messages annotated with social information based on interactive games between humans trying to generate and interpret messages for a number of different social information types and presents some classification results achieved.
Internet, Multimedia Systems and ApplicationsRepresenting emotional momentum within expressive internet communication
20 Citations2006David John, Anthony C. Boucouvalas +1 more
A prototype real-time emotional communicator that analyses the text that is input by users, extracts the emotion that is contained and outputs the parameters that are necessary to invoke an appropriate image expressing the emotion.
Journal of Media PracticeThe ‘story’ of digital excess in revolutions of the Arab Spring
19 Citations2011Tapas Ray
Research Portal (King's College London)Distinguishing affective states in weblogs
16 Citations2006Michel Généreux, Roger Evans
Using a corpus of English weblog posts, annotated for mood by their authors, support vector machine binary classifiers are trained, and it is shown that a typology of affective states proposed by Scherer’s et al is a good starting point for more refined analysis.