Enhancing sentiment analysis of financial news by detecting negation scopes

Proceedings of the Annual Hawaii International Conference on System Sciences

Volumn 2015-March, Issue , 2015, Pages 959-968

  Pröllochs, Nicolas ^a   Feuerriegel, Stefan ^a   Neumann, Dirk ^a  

^a UNIVERSITY OF FREIBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTRONIC TRADING; FINANCE; MACHINE LEARNING;

FINANCIAL NEWS; LABELED DATASET; MARKET RETURNS; POSITIVE TONE; PREDICTIVE PERFORMANCE; RULE BASED ALGORITHMS; SOURCE MATERIAL;

SENTIMENT ANALYSIS;

EID: 84944222261     PISSN: 15301605     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/HICSS.2015.119     Document Type: Conference Paper

References (28)

1. T. Loughran and B. McDonald, "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10-Ks, " The Journal of Finance, vol. 66, no. 1, pp. 35-65, 2011.
2. -, "IPO First-Day Returns, Offer Price Revisions, Volatility, and Form S-1 Language, " Journal of Financial Economics, vol. 109, no. 2, pp. 307-326, 2013.
3. P. C. Tetlock, "Giving Content to Investor Sentiment: The Role of Media in the Stock Market, " The Journal of Finance, vol. 62, no. 3, pp. 1139-1168, 2007.
4. L. Rokach, R. Romano, and O. Maimon, "Negation Recognition in Medical Narrative Reports, " Information Retrieval, vol. 11, no. 6, pp. 499-538, 2008.
5. M. Wiegand, A. Balahur, B. Roth, D. Klakow, and A. Montoyo, "A Survey on the Role of Negation in Sentiment Analysis, " in Proceedings of the Workshop on Negation and Speculation in Natural Language Processing. Stroudsburg, PA: Association for Computational Linguistics, 2010, pp. 60-68.
6. I. G. Councill, R. McDonald, and L. Velikovich, "What's Great and What's Not: Learning to Classify the Scope of Negation for Improved Sentiment Analysis, " in Proceedings of the Workshop on Negation and Speculation in Natural Language Processing. Stroudsburg, PA: Association for Computational Linguistics, 2010, pp. 51-59.
7. A. Athar, "Sentiment Analysis of Citations using Sentence Structure-Based Features, " in Proceedings of the ACL, 2011, pp. 81-87.
8. L. Jia, C. Yu, and W. Meng, "The Effect of Negation on Sentiment Analysis and Retrieval Effectiveness, " in Proceeding of the 18th ACM Conference on Information and Knowledge Management (CIKM '09), D. Cheung, Ed. New York, NY: ACM, 2009, pp. 1827-1830.
9. A. Hogenboom, P. van Iterson, B. Heerschop, F. Frasincar, and U. Kaymak, "Determining Negation Scope and Strength in Sentiment Analysis, " in Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on, 2011, pp. 2589-2594.
10. M. Taboada, J. Brooke, M. Tofiloski, K. Voll, and M. Stede, "Lexicon-Based Methods for Sentiment Analysis, " Computational Linguistics, vol. 37, no. 2, pp. 267-307, 2011.
11. M. Dadvar, C. Hauff, and F. d. Jong, "Scope of Negation Detection in Sentiment Analysis, " in Proceedings of the Dutch-Belgian Information Retrieval Workshop (DIR 2011). Amsterdam, Netherlands: University of Amsterdam, 2011, pp. 16-20.
12. W. W. Chapman, W. Bridewell, P. Hanbury, G. F. Cooper, and B. G. Buchanan, "A Simple Algorithm for Identifying Negated Findings and Diseases in Discharge Summaries, " Journal of Biomedical Informatics, vol. 34, no. 5, pp. 301-310, 2001.
13. G. Grefenstette and P. Tapanainen, "What is a Word, What is a Sentence? Problems of Tokenization, " Meylan and France, 1994.
14. C. D. Manning and H. Schütze, Foundations of Statistical Natural Language Processing. Cambridge, MA: MIT Press, 1999.
15. D. D. Lewis, Y. Yang, T. G. Rose, and F. Li, "RCV1: A New Benchmark Collection for Text Categorization Research, " Journal of Machine Learning Research, vol. 5, pp. 361-397, 2004.
16. E. Brill, "A Simple Rule-Based Part of Speech Tagger, " in Proceedings of the Workshop on Speech and Natural Language, 1992, pp. 112-116.
17. M. F. Porter, "An Algorithm for Suffix Stripping, " Program: Electronic Library and Information Systems, vol. 14, no. 3, pp. 130-137, 1980.
18. E. Blanco and D. I. Moldovan, "Some Issues on Detecting Negation from Text, " in FLAIRS Conference, 2011.
19. L. R. Rabiner, "A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition, " Proceedings of the IEEE, vol. 77, no. 2, pp. 257-286, 1989.
20. C. M. Bishop, Pattern Recognition and Machine Learning, 8th ed., ser. Information Science and Statistics. New York, NY: Springer, 2009.
21. E. Henry, "Are Investors Influenced by How Earnings Press Releases are Written?" Journal of Business Communication, vol. 45, no. 4, pp. 363-407, 2008.
22. E. A. Demers and C. Vega, "Soft Information in Earnings Announcements: News or Noise? INSEAD Working Paper No. 2010/33/AC, " SSRN Electronic Journal, 2010.
23. M. Minev, C. Schommer, and T. Grammatikos, "News and Stock Markets: A Survey on Abnormal Returns and Prediction Models, " Luxembourg, 2012.
24. M.-A. Mittermayer and G. F. Knolmayer, "Text Mining Systems for Market Response to News: A Survey, " Bern, Switzerland, 2006.
25. B. Pang and L. Lee, "Opinion Mining and Sentiment Analysis, " FNT in Information Retrieval (Foundations and Trends in Information Retrieval), vol. 2, no. 1-2, pp. 1-135, 2008.
26. S. Feuerriegel and D. Neumann, "News or Noise? How News Drives Commodity Prices, " in Proceedings of the International Conference on Information Systems (ICIS 2013). Association for Information Systems, 2013.
27. J. Muntermann and A. Guettler, "Intraday Stock Price Effects of Ad Hoc Disclosures: The German Case, " Journal of International Financial Markets, Institutions and Money, vol. 17, no. 1, pp. 1-24, 2007.
28. B. McDonald, "Loughran and McDonald Financial Sentiment Dictionary, " 2012.