SenticNet 2: A semantic and affective resource for opinion mining and sentiment analysis

Proceedings of the 25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25

Volumn , Issue , 2012, Pages 202-207

  Cambria, Erik ^a   Havasi, Catherine ^b   Hussain, Amir ^c  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b MIT MEDIA LAB   (United States)

^c UNIVERSITY OF STIRLING   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

HUMAN CONSUMPTION; IN-FIELD; MULTI-MODAL; NATURAL LANGUAGES; OPINION MINING; SEMANTIC RESOURCES; SEMANTIC-WEB TECHNIQUES; SENTIMENT ANALYSIS; SOCIAL DATA MINING; SOCIAL MEDIA; WEB 2.0;

ARTIFICIAL INTELLIGENCE; SEMANTICS;

DATA MINING;

EID: 84864992296     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (31)

1. Abbasi, A.; Chen, H.; and Salem, A. 2008. Sentiment analysis in multiple languages: Feature selection for opinion classification in web forums. ACM Transactions on Information Systems 26(3):1-34.
2. Bradley, M., and Lang, P. 1999. Affective norms for english words (ANEW): Stimuli, instruction manual and affective ratings. Technical report, The Center for Research in Psychophysiology, University of Florida.
3. Cambria, E., and Hussain, A. 2012. Sentic Computing: Techniques, Tools, and Applications. Berlin Heidelberg: Springer.
4. Cambria, E.; Hussain, A.; Havasi, C.; and Eckl, C. 2009a. AffectiveSpace: Blending common sense and affective knowledge to perform emotive reasoning. In Proceedings of CAEPIA, 32-41.
5. Cambria, E.; Hussain, A.; Havasi, C.; and Eckl, C. 2009b. Common sense computing: From the society of mind to digital intuition and beyond. volume 5707 of Lecture Notes in Computer Science. Berlin Heidelberg: Springer. 252-259.
6. Cambria, E.; Hussain, A.; Durrani, T.; Havasi, C.; Eckl, C.; and Munro, J. 2010a. Sentic computing for patient centered application. In Proceedings of IEEE ICSP, 1279-1282.
7. Cambria, E.; Hussain, A.; Havasi, C.; and Eckl, C. 2010b. SenticSpace: Visualizing Opinions and Sentiments in a Multi-Dimensional Vector Space. volume 6279 of Lecture Notes in Artificial Intelligence. Berlin Heidelberg: Springer. 385-393.
8. Cambria, E.; Speer, R.; Havasi, C.; and Hussain, A. 2010c. SenticNet: A publicly available semantic resource for opinion mining. In Proceedings of AAAI CSK, 14-18.
9. Dagan, I.; Glickman, O.; and Magnini, B. 2006. The pascal recognising textual entailment challenge. In Quiñonero-Candela, J.; Dagan, I.; Magnini, B.; and d'Alché Buc, F., eds., Machine Learning Challenges, volume 3944 of Lecture Notes in Computer Science. Berlin Heidelberg: Springer. 177-190.
10. Eckart, C., and Young, G. 1936. The approximation of one matrix by another of lower rank. Psychometrika 1(3):211-218.
11. Elliott, C. D. 1992. The Affective Reasoner: A Process Model of Emotions in a Multi-Agent System. Ph.D. Dissertation, Northwestern University, Evanston.
12. Esuli, A., and Sebastiani, F. 2006. SentiWordnet: A publicly available lexical resource for opinion mining. In Proceedings of LREC.
13. Etzioni, O.; Banko, M.; and Cafarella, M. 2006. Machine reading. In Proceedings of AAAI06.
14. Grassi, M. 2009. Developing HEO human emotions ontology. volume 5707 of Lecture Notes in Computer Science. Berlin Heidelberg: Springer. 244-251.
15. Havasi, C.; Speer, R.; and Alonso, J. 2007. ConceptNet 3: a flexible, multilingual semantic network for common sense knowledge. In Proceedings of RANLP.
16. Havasi, C.; Speer, R.; and Holmgren, J. 2010. Automated color selection using semantic knowledge. In Proceedings of AAAI CSK.
17. Hu, M., and Liu, B. 2004. Mining opinion features in customer reviews. In Proceedings of AAAI.
18. Minsky, M. 2006. The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind. Simon & Schuster.
19. Pang, B., and Lee, L. 2005. Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales. In Proceedings of ACL, 115-124.
20. Park, H., and Jun, C. 2009. A simple and fast algorithm for k-mcdoids clustering. Expert Systems with Applications 36(2):3336-3341.
21. Picard, R. 1997. Affective Computing. The MIT Press.
22. Plutchik, R. 2001. The nature of emotions. American Scientist 89(4):344-350.
23. Rao, D., and Ravichandran, D. 2009. Semi-supervised polarity lexicon induction. In Proceedings of EACL, 675-682.
24. Somasundaran, S.; Wiebe, J.; and Ruppenhofer, J. 2008. Discourse level opinion interpretation. In Proceedings of COLING.
25. Stevenson, R.; Mikels, J.; and James, T. 2007. Characterization of the affective norms for english words by discrete emotional categories. Behavior Research Methods 39:1020-1024.
26. Strapparava, C., and Valitutti, A. 2004. WordNet-Affect: an affective extension of WordNet. In Proceedings of LREC.
27. Turney, P., and Littman, M. 2003. Measuring praise and criticism: Inference of semantic orientation from association. ACM Transactions on Information Systems 21(4):315-346.
28. Velikovich, L.; Goldensohn, S.; Hannan, K.; and McDonald, R. 2010. The viability of web-derived polarity lexicons. In Proceedings of NAACL, 777-785.
29. Wall, M.; Rechtsteiner, A.; and Rocha, L. 2003. Singular value decomposition and principal component analysis. In Berrar, D.; Dubitzky, W.; and Granzow, M., eds., A Practical Approach to Microarray Data Analysis. Springer US. 91-109.
30. Wiebe, J.; Wilson, T.; and Cardie, C. 2005. Annotating expressions of opinions and emotions in language. Language Resources and Evaluation 39(2):165-210.
31. Wilson, T.; Wiebe, J.; and Hoffmann, P. 2005. Recognizing contextual polarity in phrase-level sentiment analysis. In Proceedings of HLT/EMNLP.