Lexicon-based Comments-oriented News Sentiment Analyzer system

Expert Systems with Applications

Volumn 39, Issue 10, 2012, Pages 9166-9180

  Moreo, A ^a   Romero, M ^a   Castro, J L ^a   Zurita, J M ^a  

^a UNIVERSITY OF GRANADA   (Spain)

Author keywords

Feature mining; Focus detection; Lexicon based; News analysis; Sentiment Analysis

Indexed keywords

FEATURE MINING; FOCUS DETECTION; LEXICON-BASED; NEWS ANALYSIS; SENTIMENT ANALYSIS;

C (PROGRAMMING LANGUAGE); DATA MINING;

INTERNET;

EID: 84859210660     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2012.02.057     Document Type: Article

References (64)

1. Adamic, L. A.; Glance, N. (2005). The political blogosphere and the 2004 u.s. election: Divided they blog. In Proceedings of the 3rd international workshop on link discovery (pp. 36-43). Chicago, Illinois.
2. Agrawal, R.; Rajagopalan, S.; Srikant, R.; Xu, Y. (2003). Mining newsgroups using networks arising from social behavior. In Proceedings of the 12th international conference on World Wide Web. Hungary, Budapest.
3. Archak, N.; Ghose, A.; Ipeirotis, P. G. (2007). Show me the money!: deriving the pricing power of product features by mining consumer reviews. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining. USA, San Jose, California.
4. Baroni, M.; Vegnaduzzo, S. (2004). Identifying subjective adjectives through web-based mutual information. In Proceedings of the 7th German conference on natural language processing (KONVENS'04) (pp. 613-619).
5. Benamara, F.; Cesarano, C.; Picariello, A.; Reforgiato, D.; Subrahmanian, V. (2007). Sentiment analysis: Adjectives and adverbs are better than adjectives alone. In OMNIPRESS (Ed.), Proceedings of ICWSM 2007. Boulder, Colorado.
6. B. Bickart, and R. Schindler Internet forums as influential sources of consumer information Journal of Interactive Marketing 15 2001 31 40
7. Carenini, G.; Ng, R.; Zwart, E. (2005). Extracting knowledge from evaluative text. In Proceedings of the international conference on knowledge capture (K-CAP'05) (pp. 11-18). Banff, Alberta, Canada.
8. H. Chen, and D. Zimbra Ai and opinion mining IEEE Intelligent Systems 25 2010 74 80
9. J.A. Chevalier, and D. Mayzlin The effect of word of mouth on sales: Online book reviews Journal of Marketing Research 2006 345 354
10. Choi, Y.; Breck, E.; Cardie, C. (2006). Joint extraction of entities and relations for opinion recognition. In Proceedings of the 2006 conference on empirical methods in natural language processing (EMNLP 2006) (pp. 431-439). Sydney.
11. Choi, Y.; Cardie, C. (2008). Learning with compositional semantics as structural inference for subsentential sentiment analysis. In Proceedings of the conference on empirical methods in natural language processing (EMNLP '08) (pp. 793-801). Stroudsburg, PA, USA.
12. Danescu-Niculescu-Mizil, C.; Lee, L. (2010). Dont have a clue? unsupervised co-learning of downward-entailing operators. In Proceedings of the ACL short papers (pp. 247-252).
13. Y. Dang, Y. Zhang, and H. Chen A lexicon-enhanced method for sentiment classification: An experiment on online product reviews IEEE Intelligent Systems 25 2010
14. Delort, J. (2006). Identifying commented passages of documents using implicit hyperlinks. In Proceedings of HYPERTEXT'06 (pp. 89-98). Odense, Denmark.
15. K. Denecke Using sentiwordnet for multilingual sentiment analysis Proceedings of the IEEE 24th international conference on data engineering workshop (ICDEW 2008) 2008 IEEE Computer Society 507 512
16. Denecke, K. (2009). Are sentiwordnet scores suited for multi-domain sentiment classification? In International conference on digital information management.
17. Devitt, A.; Ahmad, K. (2007). Sentiment polarity identification in financial news: A cohesion-based approach. In A. Press (Ed.), Proceedings of the 45th annual meeting association (pp. 984-991). Computational Linguistics.
18. Ding, X.; Liu, B.; Yu, P. S. (2008). A holistic lexicon-based approach to opinion mining. In Proceedings of the conference on web search and web data mining (WSDM'08) (pp. 231-239).
19. Esuli, A.; Sebastiani, F. (2005). Determining the semantic orientation of terms through gloss classification. In Proceedings of the 14th ACM international conference on Information and knowledgemanagement. Bremen, Germany.
20. Esuli, A.; Sebastiani, F. (2006). Sentiwordnet: A publicly available lexical resource for opinion mining. In Proceedings of the 5th conference on language resources and evaluation (LREC). Genova, Italy.
21. Godbole, N.; Srinivasaiah, M.; Skiena, S.; 2007. Large-scale sentiment analysis for news and blogs. In Proceedings of the international conference on weblogs and social media (ICWSM).
22. Hatzivassiloglou, V.; McKeown, K. R. (1997). Predicting the semantic orientation of adjectives. In Proceedings of 35th meeting of the association for computational linguistics (pp. 174-181). Madrid, Spain.
23. Hoffman, T. (2008). Online reputation management is hot - But is it ethical? Computerworld.
24. Hu, M.; Liu, B. (2004a). Mining and summarizing customer reviews. In Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining. USA, Seattle, WA.
25. Hu, M.; Liu, B. (2004b). Mining opinion features in customer reviews. In Proceedings of nineteenth national conference on artificial intellgience (AAAI'04).
26. Hu, M.; Sun, A.; Lim, E. (2007). Comments-oriented blog summarization by sentence extraction. In Proceedings of the sixteenth ACM conference on information and knowledge management. Portugal, Lisbon.
27. Jindal, N.; Liu, B. (2006). Mining comparative sentences and relations. In AAAI'06.
28. Jindal, N.; Liu, B. (2008). Opinion spam and analysis. In Proceedings of the conference on web search and web data mining (WSDM) (pp. 219-230). Stanford, CA.
29. Kim, S.-M.; Hovy, E. (2004). Determining the sentiment of opinions. In Proceedings of the international conference on computational linguistic (COLING). Geneva, Switzerland.
30. Kobayashi, N.; Inui, K.; Matsumoto, Y. (2007). Extracting aspect-evaluation of aspect-of relations in opinion mining. In Proceedings of the 2007 joint conference on empirical methods in natural language processing and computational natural language learning (pp. 1065-1074). Prague, Czech Republic.
31. Li, G.; Feng, J.; Wang, J.; Yu, B.; He, Y. (2008). Race: Finding and ranking compact connected trees for keyword proximity search over xml documents. In Proceedings of the 17th international world wide web conference (WWW 2008) (pp. 1045-1046). Beijing, China.
32. Liu, B.; Hsu, W.; Ma, Y. (1998). Integrating classification and association rule mining. In KDD'98.
33. L. Lloyd, A. Mehler, and S. Skiena Identifying co-referential names across large corpora Lecture Notes on Combinatorial Pattern Matching 4009 2006 12 23
34. Lue, Y.; Castellanos, M.; Dayal, U.; Zhai, C. (2011). Automatic construction of a context-aware sentiment lexicon: An optimization approach. In Proceedings of the 20th international conference on world wide web (pp. 347-356). Hyderabad, India.
35. R. Malouf, and T. Mullen Taking sides: User classification for informal online political discourse Internet Research 18 2008 177 190
36. C. Manning, and H. Schutze Foundations of statistical natural language processing 1999 In MIT Press Cambridge, Massachusetts
37. McDonald, R.; Hannan, K.; Neylon, T.; Wells, M.; Reynar, J. (2007). Structured models for fine-to-coarse sentiment analysis. In Proceedings of the 45th annual meeting of the association of computational linguistics (pp. 432-439). Prague, Czech Republic.
38. Miao, Q.; Li, Q.; Dai, R. (2008). An integration strategy for mining product features and opinions. In Proceedings of the 17th ACM conference on information and knowledge management (pp. 1369-1370). Napa Valley, California.
39. G. Miller, R. Beckwith, C. Fellbaum, D. Gross, and K. Miller Introduction to wordnet: An on-line lexical database International Journal of Lexicography (special issue) 3 1990 235 312
40. Mullen, T.; Collier, N. (2004). Sentiment analysis using support vector machines with diverse information sources. In Proceedings of EMNLP (pp. 412-418).
41. Nasukawa, T.; Yi, J. (2003). Sentiment analysis: capturing favorability using natural language processing. In Proceedings of the 2nd international conference on Knowledge capture. USA, Sanibel Island, FL.
42. A. Neviarouskaya, H. Prendinger, and M. Ishizuka Sentiful: A lexicon for sentiment analysis IEEE Transactions on Affective Computing 2 2011 22 36
43. Ohana, B.; Tierney, B. (2009). Sentiment classification of reviews using sentiwordnet. In 9th. IT&T conference.
44. B. Pang, and L. Lee Opinion mining and sentiment analysis Foundations and Trends in Information Retrieval 2 2008 1 135
45. B. Pang, L. Lee, and S. Vaithyanathan Thumbs up? Sentiment classification using machine learning techniques Proceedings of the conference on empirical methods in natural language processing (EMNLP) 2002 Association for Computational Linguistics Philadelphia 79 86
46. Popescu, A.; Etzioni, O. (2005). Extracting product features and opinions from reviews. In Proceedings of EMNLP (pp. 339-346).
47. Qiu, G.; Liu, B.; Bu, J.; Chen, C. (2009). Expanding domain sentiment lexicon through double propagation. In Proceedings of the 21st international joint conferences on artificial intelligence (pp. 1199-1204). Pasadena, California.
48. M. Taboada, J. Brooke, M. Tofiloski, K. Voll, and M. Stede Lexicon-based methods for sentiment analysis Computational Linguistics 37 2011 267 307
49. S. Tan, and Y. Wang Weighted scl model for adaptation of sentiment classification Expert Systems with Applications 38 2011 10524 10531
50. S. Tan, and Q. Wu A random walk algorithm for automatic construction of domain-oriented sentiment lexicon Expert Systems with Applications 38 2011 12094 12100
51. S. Tan, and J. Zhang An empirical study of sentiment analysis for chinese documents Expert Systems with Applications 34 2008 2622 2629
52. Täckström, O.; McDonald, R. (2011). Semi-supervised latent variable models for sentence-level sentiment analysis. In Proceedings of the 49th annual meeting of the association for computational linguistics (pp. 569-574). Portland, Oregon.
53. Titov, I.; McDonald, R. (2008). A joint model of text and aspect ratings for sentiment summarization. In The 46th annual meeting of the association for computational linguistic (pp. 308-316). Columbus, Ohio.
54. Turney, P. D. (2002). Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews. In Proceedings of the 40th annual meeting on association for computational linguistics. Philadelphia, Pennsylvania.
55. Velikovich, L.; Blair-Goldensohn, S.; Hannan, K.; McDonald, R. (2010). The viability of web-derived polarity lexicons. In The 2010 annual conference of the North American chapter of the ACL (pp. 777-785). Los Angeles, California.
56. J. Wiebe, T. Wilson, R. Bruce, M. Bell, and M. Martin Learning subjective language Computational Linguistics 30 2004 277 308
57. J. Wiebe, T. Wilson, and C. Cardie Annotating expressions of opinions and emotions in language Language Resources and Evaluation 2 2005 165 210
58. Wilson, T.; Wiebe, J.; Hoffmann, P. (2005). Recognizing contextual polarity in phrase-level sentiment analysis. In Proceedings of human language technology conference and conference on empirical methods in natural language processing (HLT/EMNLP) (pp. 347-354). Vancouver.
59. Wilson, T.; Wiebe, J.; Hwa, R. (2004). Just how mad are you? finding strong and wake opinion clauses. In Proceedings of AAAI (pp. 761-769). San Jose, CA.
60. Q. Wu, and S. Tan A two-stage framework for cross-domain sentiment classification Expert Systems with Applications 38 2011 14269 14275
61. Yessenalina, A.; Yue, Y.; Cardie, C. (2010). Multi-level structured models for document-level sentiment classification. In Proceedings of the 2010 conference on empirical methods in natural language processing (pp. 1046-1056). Massachusetts, USA.
62. Yi, J.; Nasukawa, T.; Bunescu, R.; Niblack, W. (2003). Sentiment analyzer: Extracting sentiments about a given topic using natural language processing techniques. In Proceedings of the third IEEE international conference on data mining.
63. Z. Zhai, H. Xu, B. Kang, and P. Jia Exploiting effective features for chinese sentiment classification Expert Systems with Applications 38 2011 9139 9146
64. Zhang, Z.; Varadarajan, B. (2006). Utility scoring of product reviews. In Proceedings of the 15th ACM international conference on Information and knowledge management. USA, Arlington, Virginia.