Meta-level sentiment models for big social data analysis

Author:

Bravo-Marquez Felipe,Mendoza Marcelo,Poblete Barbara

Funder

FONDEF-CONICYT

FONDECYT

Millennium Nucleus Center for Semantic Web Research

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference35 articles.

1. S. Baccianella, A. Esuli, F. Sebastiani, Sentiwordnet 3.0: an enhanced lexical resource for sentiment analysis and opinion mining, in: Proceedings of the Seventh International Conference on Language Resources and Evaluation, Valletta, Malta, 2010.

2. R. Baeza-Yates, L. Rello, How Bad Do You Spell?: The Lexical Quality of Social Media, The Future of the Social Web, Papers from the 2011 ICWSM Workshop, Barcelona, Catalonia, Spain, AAAI Workshops, 2011.

3. M.M. Bradley, P.J. Lang, Affective Norms for English Words (ANEW) Instruction Manual and Affective Ratings, Technical Report C-1, The Center for Research in Psychophysiology University of Florida, 2009.

4. F. Bravo-Marquez, M. Mendoza, B. Poblete, Combining strengths, emotions and polarities for boosting Twitter sentiment analysis, in: Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining, WISDOM ’13, New York, USA, 2013, pp. 2:1–2:9.

5. E. Cambria, R. Speer C. Havasi, A. Hussain, SenticNet 2: a semantic and affective resource for opinion mining and sentiment analysis, in: FLAIRS Conference, 2012, pp. 202–207.

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