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2010 sentiwordnet 30 an enhanced lexical resource for

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Unformatted text preview: urence Fishbourne is not so good either, I was surprised. 33 Sentiment Analysis A Baseline Algorithm Sentiment Analysis Sen+ment Lexicons Dan Jurafsky The General Inquirer Philip J. Stone, Dexter C Dunphy, Marshall S. Smith, Daniel M. Ogilvie. 1966. The General Inquirer: A Computer Approach to Content Analysis. MIT Press •  •  •  •  Home page: hXp://www.wjh.harvard.edu/~inquirer List of Categories: hXp://www.wjh.harvard.edu/~inquirer/homecat.htm Spreadsheet: hXp://www.wjh.harvard.edu/~inquirer/inquirerbasic.xls Categories: •  Posi+v (1915 words) and Nega+v (2291 words) •  Strong vs Weak, Ac+ve vs Passive, Overstated versus Understated •  Pleasure, Pain, Virtue, Vice, Mo+va+on, Cogni+ve Orienta+on, etc •  Free for Research Use Dan Jurafsky LIWC (Linguis%c Inquiry and Word Count) Pennebaker, J.W., Booth, R.J., & Francis, M.E. (2007). Linguis+c Inquiry and Word Count: LIWC 2007. Aus+n, TX •  Home page: hXp://www.liwc.net/ •  2300 words, >70 classes •  Affec%ve Processes •  nega+ve emo+on (bad, weird, hate, problem, tough) •  posi+ve emo+on (love, nice, sweet) •  Cogni%ve Processes •  Tenta+ve (maybe, perhaps, guess), Inhibi+on (block, constraint) •  Pronouns, Nega%on (no, never), Quan%fiers (few, many) •  $30 or $90 fee Dan Jurafsky MPQA Subjec%vity Cues Lexicon Theresa Wilson, Janyce Wiebe, and Paul Hoffmann (2005). Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis. Proc. of HLT-EMNLP-2005. Riloff and Wiebe (2003). Learning extraction patterns for subjective expressions. EMNLP-2003. •  Home page: hXp://www.cs.piX.edu/mpqa/subj_lexicon.html •  6885 words from 8221 lemmas •  2718 posi+ve •  4912 nega+ve •  Each word annotated for intensity (strong, weak) •  GNU GPL 38 Dan Jur...
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