Building emotional dictionary for sentiment analysis of online news

World Wide Web

Volumn 17, Issue 4, 2014, Pages 723-742

  Rao, Yanghui ^a   Lei, Jingsheng ^b   Wenyin, Liu ^b   Li, Qing ^a   Chen, Mingliang ^a  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

^b SHANGHAI UNIVERSITY OF ELECTRIC POWER   (China)

Author keywords

Emotional dictionary; Social emotion detection; Topic modeling; Web 2.0

Indexed keywords

ALGORITHMS; VIRTUAL REALITY;

HUMAN EMOTION; NEWS ARTICLES; ON-LINE DOCUMENTS; PRUNING STRATEGY; SENTIMENT ANALYSIS; SOCIAL EMOTIONS; TOPIC MODELING; WEB 2.0;

DATA MINING;

EID: 84902327925     PISSN: 1386145X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11280-013-0221-9     Document Type: Article

References (32)

1. Baccianella S., Esuli A., Sebastiani F.: SentiWordNet 3. 0: An enhanced lexical resource for sentiment analysis and opinion mining. In: Proceedings of The 7th Conference on Language Resources and Evaluation, pp. 2200-2204, (2010).
2. Banea, C., Mihalcea R., Wiebe J.: A bootstrapping method for building subjectivity lexicons for languages with scarce resources. In: Proceedings of The 6th International Conference on Language Resources and Evaluation, (2008).
3. Bao, S., Xu, S., Zhang, L., Yan, R., Su, Z., Han, D., Yu, Y.: Mining social emotions from affective text. IEEE Trans. Knowl. Data Eng. 24, 1658-1670 (2011).
4. Bao, S., Xu, S., Zhang, L., Yan, R., Su, Z., Han, D., Yu Y.: Joint emotion-topic modeling for social affective text mining. In: Proceedings of The 9th IEEE International Conference on Data Mining, pp. 699-704, (2009).
5. Blei, D. M., Ng, A. Y., Jordan, M. I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3, 993-1022 (2003).
6. Cai, D., Mei, Q., Han, J., Zhai, C.: Modeling hidden topics on document manifold. In: Proceedings of The 17th ACM Conference on Information and Knowledge Management, pp. 911-920, (2008).
7. Chaumartin, F. R.: Upar7: A knowledge-based system for headline sentiment tagging. In: The 4th International Workshop on Semantic Evaluations, 422-425, Association for Computational Linguistics, (2007).
8. Das, S., Chen, M.: Yahoo! for Amazon: Extracting market sentiment from stock message boards. In: Proceedings of The 8th Asia Pacific Finance Association Annual Conference, (2001).
9. Griffiths T. L., Steyvers, M.: Finding scientific topics. In: Proceedings of the National Academy of Sciences of the United States of America, 101, pp. 5228-5235, (2004).
10. Hofmann, T.: Probabilistic latent semantic indexing. In Proceedings of The 22nd annual international ACM SIGIR conference on Research and development in information retrieval, pp. 50-57, (1999).
11. Ifrim, G., Weikum, G.: The bag-of-opinions method for review rating prediction from sparse text patterns. In: Proceedings of Coling, (2010).
12. Jindal, N., Liu, B.: Opinion spam and analysis. In: The International Conference on Web Search and Web Data Mining, pp. 219-230, (2008).
13. Katz, P., Singleton, M., Wicentowski, R.: Swat-mp: The semeval-2007 systems for task 5 and task 14, In: The 4th International Workshop on Semantic Evaluations, 308-313. Association for Computational Linguistics, (2007).
14. Koga, H., Taniguchi, T.: Developing a user recommendation engine on twitter using estimated latent topics. In: Proceedings of The 14th international conference on Human-computer interaction: design and development approaches - vol. Part I, pp. 461-470, (2011).
15. Kolya, A., Das, D., Ekbal, A., Bandyopadhyay, S.: Identifying event-sentiment association using lexical equivalence and co-reference approaches. In: Workshop on Relational Models of Semantics Collocated with ACL, pp. 19-27, (2011).
16. Lin, K. H.-Y., Yang, C., Chen, H.-H.: Emotion classification of online news articles from the reader's perspective. In: IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, pp. 220-226, (2008).
17. Lin, K. H.-Y., Yang, C., Chen, H.-H.: What emotions do news articles trigger in their readers?. In: Proceedings of The 30th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 733-734, (2007).
18. Liu, J., Seneff, S.: Review sentiment scoring via a parse-and-paraphrase paradigm. In: Empirical methods in natural language processing, ACL, (2009).
19. Manning, C. D., Raghavan, P., Schütze, H.: Introduction to information retrieval. Cambridge University Press, pp. 156-281, (2008).
20. Moreo, A., Romero, M., Castro, J. L., Zurita, J. M.: Lexicon-based comments-oriented news sentiment analyzer system. Expert Syst. Appl. 39, 9166-9180 (2012).
21. Neviarouskaya, A., Prendinger, H., Ishizuka, M.: Affect analysis model: novel rule-based approach to affect sensing from text. Nat. Lang. Eng. 17(1), 95-135 (2011).
22. Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up? Sentiment classification using machine learning techniques. In: Empirical methods in natural language processing, pp. 79-86, (2002).
23. Rosen-Zvi, M., Griffiths, T., Steyvers, M., Smyth, P.: The author-topic model for authors and documents. In: Proceedings of The 20th Conference in Uncertainty in Artificial Intelligence, pp. 487-494, (2004).
24. Smet, W. D., Moens, M. -F.: An aspect based document representation for event clustering. In: Proceedings of The 19th meeting of Computational Linguistics, (2009).
25. Snow, R., Connor, B. O', Jurafsky, D., Ng, A. Y.: Cheap and fast-but is it good? Evaluation non-expert annotations for natural language tasks. In: Empirical Methods in Natural Language Processing, pp. 254-263, (2008).
26. Song, Y., Wang, H., Wang, Z., Li, H., Chen, W.: Short text conceptualization using a probabilistic knowledgebase. In: Proceedings of the International Joint Conference on Artificial Intelligence, pp. 2330-2336, (2011).
27. Strapparava, C., Mihalcea, R.: Learning to identify emotions in text. In: Proceedings of the 2008 ACM Symposium on Applied Computing, Fortaleza, Brazil, pp. 1556-1560, (2008).
28. Strapparava, C., Mihalcea, R.: Semeval-2007 task 14: Affective text. In: Proceedings of The 4th International Workshop on Semantic Evaluations, pp. 70-74, (2007).
29. Strapparava, C., Valitutti, A.: Wordnet-affect: an affective extension of wordnet. In: Proceedings of The 4th International Conference on Language Resources and Evaluation, pp. 1083-1086, (2004).
30. Tong, R. M.: An operational system for detecting and tracking opinions in on-line discussions. In: Working Notes of the ACM SIGIR 2001 Workshop on Operational Text Classification, pp. 1-6, (2001).
31. Turney, P. D., Littman, M. L.: Unsupervised learning of semantic orientation from a hundred-billion-word corpus, Technical Report EGB-1094, National Research Council Canada, (2002).
32. Turney, P. D.: Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews. In: Proceedings of The 40th annual meeting of the Association for Computational Linguistics, pp. 17-424, (2002).