Wan2tlk?: everyday text messaging
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Characterizing debate performance via aggregated twitter sentiment
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The viability of web-derived polarity lexicons
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
An unsupervised aspect-sentiment model for online reviews
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Classifying sentiment in microblogs: is brevity an advantage?
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Robust sentiment detection on Twitter from biased and noisy data
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Network properties and social sharing of emotions in social awareness streams
Proceedings of the ACM 2011 conference on Computer supported cooperative work
Happiness is assortative in online social networks
Artificial Life
Emotion tokens: bridging the gap among multilingual twitter sentiment analysis
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
Improving tweet stream classification by detecting changes in word probability
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Learning from bullying traces in social media
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
A broad-coverage normalization system for social media language
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Leveraging viewer comments for mood classification of music video clips
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Unsupervised sentiment analysis with emotional signals
Proceedings of the 22nd international conference on World Wide Web
Sentiment analysis on evolving social streams: how self-report imbalances can help
Proceedings of the 7th ACM international conference on Web search and data mining
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We present an automatic method which leverages word lengthening to adapt a sentiment lexicon specifically for Twitter and similar social messaging networks. The contributions of the paper are as follows. First, we call attention to lengthening as a widespread phenomenon in microblogs and social messaging, and demonstrate the importance of handling it correctly. We then show that lengthening is strongly associated with subjectivity and sentiment. Finally, we present an automatic method which leverages this association to detect domain-specific sentiment- and emotion-bearing words. We evaluate our method by comparison to human judgments, and analyze its strengths and weaknesses. Our results are of interest to anyone analyzing sentiment in microblogs and social networks, whether for research or commercial purposes.