Computational Extraction of Social and Interactional Meaning 2011 INTERNATIONAL SUMMER SCHOOL IN Language and Speech Technologies (SSLST 2011) Tarragona, Spain

COURSE INFORMATION
Instructor	Dan Jurafsky, jurafsky@stanford.edu
When	Monday August 29, 12:00-14:00 and 20:00-22:00 Tuesday August 30, 12:00-14:00 and 20:00-22:00
Description	This course introduces methods for extracting social or affective meaning from text and speech. We will cover literature on most of the classes of affective meaning in Scherer's standard typology: sentiment, i.e. enduring, affectively colored preferences or attitudes (likes, dislikes), personality traits (extroverted, anxious, agreeable), brief evaluative episodes like emotions (anger, joy, shame), and interpersonal stances taken toward another person in a conversation (friendly, cold, flirtatious). We will analyze the linguistic cues from text and speech (lexical, dialog act, prosodic, spectral) that signal these kinds of meaning.

	SCHEDULE
#	Lec	Topic and Readings
1	Lec 1 slides	Sentiment Lexicons and Sentiment Classification Hatzivassiloglou, Vasileios and Kathleen R. McKeown. 1997. Predicting the semantic orientation of adjectives. In Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics, 174-181. Pang, Bo, Lee, Lillian, and Vaithyanathan, Shivakumar. 2002. Thumbs up? Sentiment classification using machine learning techniques. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 79-86. ACL.
2	Lec 2 slides Prosody Lec	Prosody, Emotion, and Mood Scherer, K. R. 2003. Vocal communication of emotion: A review of research paradigms. Speech Communication 40:1-2, 227-256. Braun, Angelika and Matthias Katerbow. 2005. Emotions in dubbed speech: An intercultural approach with respect to F0. Interspeech 2005, 521-524. J. Ang, R. Dhillon, A. Krupski, E. Shriberg, and A. Stolcke. 2002. Prosody-Based Automatic Detection of Annoyance and Frustration in Human-Computer Dialog. Interspeech 2002.
3	Lec 3 slides	Personality and Interpersonal Stance F. Mairesse, M. Walker, M. Mehl, and R. Moore. 2007. Using linguistic cues for the automatic recognition of personality in conversation and text. Journal of Artificial Intelligence Research (JAIR), 30:457-500. Read at least 457-468 and 490-493 Rajesh Ranganath, Dan Jurafsky, and Dan McFarland. 2011 submitted ms. Detecting Friendly, Flirtatious, Awkward, and Assertive Speech in Speed-Dates.. Read pages 1-16, 20, 24, and 30-35.
4	Lec 4 slides	Sarcasm and Agreement Tepperman, Joseph, David Traum, and Shrikanth Narayanan. 2006. Yeah right: Sarcasm recognition for spoken dialogue systems. ICSLP 2006. S. Benus, A. Gravano, and J. Hirschberg, 2007. Prosody, emotions, and...`whatever'," Proc. Interspeech D. Davidov, O. Tsur, and A. Rappoport. 2010. Semi-supervised recognition of sarcastic sentences in Twitter and Amazon. Proc. of the Fourteenth Conference on Computational Natural Language Learning, pp. 107-116. Roberto Gonzalez-Ibanez, Smaranda Muresan, Nina Wacholder (2011). Identifying Sarcasm in Twitter: A Closer Look. Proceedings of ACL-HTL 2011 (short paper).