Topic modeling based sentiment analysis on social media for stock market prediction

ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference

Volumn 1, Issue , 2015, Pages 1354-1364

  Nguyen, Thien Hai ^a   Shirai, Kiyoaki ^a  

^a JAPAN ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; FINANCIAL MARKETS; FORECASTING; SENTIMENT ANALYSIS;

PREDICTION MODEL; SOCIAL MEDIA; STOCK MARKET PREDICTION; STOCK PREDICTIONS; STOCK PRICE MOVEMENTS; TOPIC MODELING;

SOCIAL NETWORKING (ONLINE);

EID: 84943756361     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/v1/p15-1131     Document Type: Conference Paper

References (29)

1. Werner Antweiler and Murray Z Frank. 2004. Is all that talk just noise? the information content of internet stock message boards. The Journal of Finance, 59(3):1259-1294.
2. Stefano Baccianella, Andrea Esuli, and Fabrizio Sebastiani. 2010. Sentiwordnet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining. In Proceedings of the Seventh Conference on International Language Resources and Evaluation (LREC10), volume 10, pages 2200-2204.
3. David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2003. Latent dirichlet allocation. Journal of Machine Learning Research, 3:993-1022.
4. Johan Bollen, Huina Mao, and Xiaojun Zeng. 2011. Twitter mood predicts the stock market. Journal of Computational Science, 2(1):1-8.
5. Eugene F Fama, Lawrence Fisher, Michael C Jensen, and Richard Roll. 1969. The adjustment of stock prices to new information. International economic review, 10(1):1-21.
6. Eugene F Fama. 1991. Efficient capital markets: Ii. The journal of finance, 46(5):1575-1617.
7. Yohan Jo and Alice H Oh. 2011. Aspect and sentiment unification model for online review analysis. In Proceedings of the fourth ACM international conference on Web search and data mining, pages 815-824. ACM.
8. Thorsten Joachims. 1998. Text categorization with support vector machines: Learning with many relevant features. Springer.
9. Himabindu Lakkaraju, Chiranjib Bhattacharyya, Indrajit Bhattacharya, and Srujana Merugu. 2011. Exploiting coherence for the simultaneous discovery of latent facets and associated sentiments. In Proceedings of the Eleventh SIAM International Conference on Data Mining, SDM 2011, April 28-30, 2011, Mesa, Arizona, USA, pages 498-509. SIAM /Omnipress.
10. Chenghua Lin and Yulan He. 2009. Joint sentiment/topic model for sentiment analysis. In Proceedings of the 18th ACM conference on Information and knowledge management, pages 375-384. ACM.
11. Bing Liu and Lei Zhang. 2012. A survey of opinion mining and sentiment analysis. In Mining Text Data, pages 415-463. Springer.
12. Christopher D. Manning, Mihai Surdeanu, John Bauer, Jenny Finkel, Steven J. Bethard, and David Mc-Closky. 2014. The Stanford CoreNLP natural language processing toolkit. In Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 55-60.
13. Thien Hai Nguyen and Kiyoaki Shirai. 2013. Text classification of technical papers based on text segmentation. In Elisabeth Mtais, Farid Meziane, Mohamad Saraee, Vijayan Sugumaran, and Sunil Vadera, editors, Natural Language Processing and Information Systems, volume 7934 of Lecture Notes in Computer Science, pages 278-284. Springer Berlin Heidelberg.
14. Thien Hai Nguyen and Kiyoaki Shirai. 2015. Aspectbased sentiment analysis using tree kernel based relation extraction. In Alexander Gelbukh, editor, Computational Linguistics and Intelligent Text Processing, volume 9042 of Lecture Notes in Computer Science, pages 114-125. Springer International Publishing.
15. Bo Pang and Lillian Lee. 2008. Opinion mining and sentiment analysis. Foundations and trends in information retrieval, 2(1-2):1-135.
16. Bo Qian and Khaled Rasheed. 2007. Stock market prediction with multiple classifiers. Applied Intelligence, 26(1):25-33.
17. Michael Rechenthin, W Nick Street, and Padmini Srinivasan. 2013. Stock chatter: Using stock sentiment to predict price direction. Algorithmic Finance, 2(3):169-196.
18. Robert P Schumaker and Hsinchun Chen. 2009a. A quantitative stock prediction system based on financial news. Information Processing & Management, 45(5):571-583.
19. Robert P. Schumaker and Hsinchun Chen. 2009b. Textual analysis of stock market prediction using breaking financial news: The azfin text system. ACM Trans. Inf. Syst., 27(2):12:1-12:19, March.
20. Jianfeng Si, Arjun Mukherjee, Bing Liu, Qing Li, Huayi Li, and Xiaotie Deng. 2013. Exploiting topic based twitter sentiment for stock prediction. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, ACL 2013, 4-9 August 2013, Sofia, Bulgaria, Volume 2: Short Papers, pages 24-29. The Association for Computer Linguistics.
21. George Tsibouris and Matthew Zeidenberg. 1995. Testing the efficient markets hypothesis with gradient descent algorithms. In Neural Networks in the Capital Markets, pages 127-136.Wiley: Chichester.
22. Robert Tumarkin and Robert F Whitelaw. 2001. News or noise? internet postings and stock prices. Financial Analysts Journal, 57(3):41-51.
23. Tien Thanh Vu, Shu Chang, Quang Thuy Ha, and Nigel Collier. 2012. An experiment in integrating sentiment features for tech stock prediction in twitter. In 24th International Conference on Computational Linguistics, pages 23-38.
24. Steven Walczak. 2001. An empirical analysis of data requirements for financial forecasting with neural networks. Journal of management information systems, 17(4):203-222.
25. Boyi Xie, Rebecca J Passonneau, Leon Wu, and Germán Creamer. 2013. Semantic frames to predict stock price movement. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, pages 873-883.
26. Xue Zhang, Hauke Fuehres, and Peter A Gloor. 2011. Predicting stock market indicators through twitter "I hope it is not as bad as I fear". Procedia-Social and Behavioral Sciences, 26(0):55-62.
27. Wayne Xin Zhao, Jing Jiang, Hongfei Yan, and Xiaoming Li. 2010. Jointly modeling aspects and opinions with a maxent-lda hybrid. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pages 56-65. Association for Computational Linguistics.
28. Yi Zuo and Eisuke Kita. 2012a. Stock price forecast using bayesian network. Expert Systems with Applications: An International Journal, 39(8):6729-6737.
29. Yi Zuo and Eisuke Kita. 2012b. Up/down analysis of stock index by using bayesian network. Engineering Management Research, 1(2):46-52.