ToDo List: Reference List about Sentiment Analysis

Topic: Application of Sentiment Analysis and Machine Learning in Finance

  • : Unread
  • : Extensive Reading
  • : Intensive Reading

Social Science

  1. Scherer, Klaus R (2005). What are emotions? And how can they be measured?. Social science information, 44(4), 695—729

Marketing/Management Science

  1. Godes, David, Mayzlin, Dina (2004). Using online conversations to study word-of-mouth communication. Marketing science, 23(4), 545—560
  2. Chevalier, Judith A, Mayzlin, Dina (2006). The effect of word of mouth on sales: Online book reviews. Journal of marketing research, 43(3), 345—354
  3. Das, Sanjiv R, Chen, Mike Y (2007). Yahoo! for Amazon: Sentiment extraction from small talk on the web. Management science, 53(9), 1375—1388
  4. Archak, Nikolay, Ghose, Anindya, Ipeirotis, Panagiotis G (2011). Deriving the pricing power of product features by mining consumer reviews. Management science, 57(8), 1485—1509
  5. Ghose, Anindya, Han, Sang Pil (2011). An empirical analysis of user content generation and usage behavior on the mobile Internet. Management Science, 57(9), 1671—1691


  1. Barberis, Nicholas, Shleifer, Andrei, Vishny, Robert (1998). A model of investor sentiment. Journal of financial economics, 49(3), 307—343
  2. Seo, Young-Woo, Giampapa, Joseph, Sycara, Katia (2002). Text classification for intelligent portfolio management.
  3. Seo, Young-Woo, Giampapa, Joseph A, Sycara, Katia (2004). Financial news analysis for intelligent portfolio management.
  4. Antweiler, Werner, Frank, Murray Z (2004). Is all that talk just noise? The information content of internet stock message boards. The Journal of Finance, 59(3), 1259—1294
  5. Tetlock, Paul C, Saar-Tsechansky, Maytal, Macskassy, Sofus (2008). More than words: Quantifying language to measure firms’ fundamentals. The Journal of Finance, 63(3), 1437—1467
  6. Fang, Lily, Peress, Joel (2009). Media coverage and the cross-section of stock returns. The Journal of Finance, 64(5), 2023—2052
  7. Engelberg, Joseph E, Parsons, Christopher A (2011). The causal impact of media in financial markets. The Journal of Finance, 66(1), 67—97
  8. Engelberg, Joseph E, Reed, Adam V, Ringgenberg, Matthew C (2012). How are shorts informed?: Short sellers, news, and information processing. Journal of Financial Economics, 105(2), 260—278
  9. Das, Sanjiv Ranjan, others, (2014). Text and context: Language analytics in finance. Foundations and Trends{\textregistered} in Finance, 8(3), 145—261


  1. Stewart, Katherine J (2006). How hypertext links influence consumer perceptions to build and degrade trust online. Journal of Management Information Systems, 23(1), 183—210
  2. Forman, Chris, Ghose, Anindya, Wiesenfeld, Batia (2008). Examining the relationship between reviews and sales: The role of reviewer identity disclosure in electronic markets. Information Systems Research, 19(3), 291—313
  3. Duan, Wenjing, Gu, Bin, Whinston, Andrew B (2009). Informational cascades and software adoption on the internet: an empirical investigation. Mis Quarterly, (), 23—48
  4. Yang, Christopher C, Tang, Xuning, Wong, YC, Wei, Chih-Ping (2010). Understanding online consumer review opinions with sentiment analysis using machine learning. Pacific Asia Journal of the Association for Information Systems, 2(3)
  5. Chau, Michael, Xu, Jennifer (2012). Business intelligence in blogs: Understanding consumer interactions and communities.. MIS quarterly, 36(4)
  6. Chen, Hailiang, De, Prabuddha, Hu, Yu Jeffrey, Hwang, Byoung-Hyoun (2013). Customers as advisors: The role of social media in financial markets.
  7. Stieglitz, Stefan, Dang-Xuan, Linh (2013). Emotions and information diffusion in social media—sentiment of microblogs and sharing behavior. Journal of Management Information Systems, 29(4), 217—248
  8. Goh, Khim-Yong, Heng, Cheng-Suang, Lin, Zhijie (2013). Social media brand community and consumer behavior: Quantifying the relative impact of user-and marketer-generated content. Information Systems Research, 24(1), 88—107
  9. Luo, Xueming, Zhang, Jie, Duan, Wenjing (2013). Social media and firm equity value. Information Systems Research, 24(1), 146—163
  10. Chen, Hailiang, De, Prabuddha, Hu, Yu, Hwang, Byoung-Hyoun (2014). Wisdom of crowds: The value of stock opinions transmitted through social media. The Review of Financial Studies, 27(5), 1367—1403
  11. Ghiassi, Manoochehr, Zimbra, David, Lee, Sean (2016). Targeted Twitter Sentiment Analysis for Brands Using Supervised Feature Engineering and the Dynamic Architecture for Artificial Neural Networks. Journal of Management Information Systems, 33(4), 1034—1058


  1. Duan, Wenjing, Gu, Bin, Whinston, Andrew B (2008). Do online reviews matter?-An empirical investigation of panel data. Decision support systems, 45(4), 1007—1016
  2. Martens, David, Bruynseels, Liesbeth, Baesens, Bart, Willekens, Marleen, Vanthienen, Jan (2008). Predicting going concern opinion with data mining. Decision Support Systems, 45(4), 765—777
  3. Li, Nan, Wu, Desheng Dash (2010). Using text mining and sentiment analysis for online forums hotspot detection and forecast. Decision support systems, 48(2), 354—368
  4. Groth, Sven S, Muntermann, Jan (2011). An intraday market risk management approach based on textual analysis. Decision Support Systems, 50(4), 680—691
  5. Cao, Qing, Duan, Wenjing, Gan, Qiwei (2011). Exploring determinants of voting for the “helpfulness” of online user reviews: A text mining approach. Decision Support Systems, 50(2), 511—521
  6. Schumaker, Robert P, Zhang, Yulei, Huang, Chun-Neng, Chen, Hsinchun (2012). Evaluating sentiment in financial news articles. Decision Support Systems, 53(3), 458—464
  7. Duric, Adnan, Song, Fei (2012). Feature selection for sentiment analysis based on content and syntax models. Decision Support Systems, 53(4), 704—711
  8. Maks, Isa, Vossen, Piek (2012). A lexicon model for deep sentiment analysis and opinion mining applications. Decision Support Systems, 53(4), 680—688
  9. Montoyo, Andr{\’e}s, Mart{\’\i}Nez-Barco, Patricio, Balahur, Alexandra (2012). Subjectivity and sentiment analysis: An overview of the current state of the area and envisaged developments. Decision Support Systems
  10. Yu, Yang, Duan, Wenjing, Cao, Qing (2013). The impact of social and conventional media on firm equity value: A sentiment analysis approach. Decision Support Systems, 55(4), 919—926
  11. Hagenau, Michael, Liebmann, Michael, Neumann, Dirk (2013). Automated news reading: Stock price prediction based on financial news using context-capturing features. Decision Support Systems, 55(3), 685—697
  12. Wang, Gang, Sun, Jianshan, Ma, Jian, Xu, Kaiquan, Gu, Jibao (2014). Sentiment classification: The contribution of ensemble learning. Decision support systems, 57(), 77—93
  13. Khan, Farhan Hassan, Bashir, Saba, Qamar, Usman (2014). TOM: Twitter opinion mining framework using hybrid classification scheme. Decision Support Systems, 57(), 245—257
  14. Da Silva, Nadia FF, Hruschka, Eduardo R, Hruschka, Estevam R (2014). Tweet sentiment analysis with classifier ensembles. Decision Support Systems, 66(), 170—179


  1. Ghiassi, Manoochehr, Skinner, James, Zimbra, David (2013). Twitter brand sentiment analysis: A hybrid system using n-gram analysis and dynamic artificial neural network. Expert Systems with applications, 40(16), 6266—6282
  2. Nassirtoussi, Arman Khadjeh, Aghabozorgi, Saeed, Wah, Teh Ying, Ngo, David Chek Ling (2014). Text mining for market prediction: A systematic review. Expert Systems with Applications, 41(16), 7653—7670
  3. Cavalcante, Rodolfo C, Brasileiro, Rodrigo C, Souza, Victor LF, Nobrega, Jarley P, Oliveira, Adriano LI (2016). Computational intelligence and financial markets: A survey and future directions. Expert Systems with Applications, 55(), 194—211


  1. Hatzivassiloglou, Vasileios, McKeown, Kathleen R (1997). Predicting the semantic orientation of adjectives. , (), 174—181
  2. Pang, Bo, Lee, Lillian, Vaithyanathan, Shivakumar (2002). Thumbs up?: sentiment classification using machine learning techniques, 79—86
  3. Turney, Peter D (2002). Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews. , (), 417—424
  4. Riloff, Ellen, Wiebe, Janyce (2003). Learning extraction patterns for subjective expressions. , (), 105—112
  5. Hu, Minqing, Liu, Bing (2004). Mining and summarizing customer reviews. , (), 168—177
  6. Kim, Soo-Min, Hovy, Eduard (2004). Determining the sentiment of opinions. , (), 1367
  7. Wilson, Theresa, Wiebe, Janyce, Hoffmann, Paul (2005). Recognizing contextual polarity in phrase-level sentiment analysis. , (), 347—354
  8. Wiebe, Janyce, Riloff, Ellen (2005). Creating Subjective and Objective Sentence Classifiers from Unannotated Texts.. , 5(), 486—497
  9. Schumaker, Robert P, Chen, Hsinchun (2009). Textual analysis of stock market prediction using breaking financial news: The AZFin text system. ACM Transactions on Information Systems (TOIS), 27(2), 12
  10. Go, Alec, Bhayani, Richa, Huang, Lei (2009). Twitter sentiment classification using distant supervision. CS224N Project Report, Stanford, 1(2009), 12
  11. Potts, Christopher (2010). On the negativity of negation. , 20(), 636—659
  12. Cambria, Erik, Schuller, Bj{\”o}rn, Xia, Yunqing, Havasi, Catherine (2013). New avenues in opinion mining and sentiment analysis. IEEE Intelligent Systems, 28(2), 15—21
  13. Baccianella, Stefano, Esuli, Andrea, Sebastiani, Fabrizio (2010). SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining.. , 10(), 2200—2204
  14. Chen, Hsinchun, Zimbra, David (2010). AI and opinion mining. IEEE Intelligent Systems, 25(3), 74—80
  15. Bollen, Johan, Mao, Huina, Zeng, Xiaojun (2011). Twitter mood predicts the stock market. Journal of computational science, 2(1), 1—8
  16. Taboada, Maite, Brooke, Julian, Tofiloski, Milan, Voll, Kimberly, Stede, Manfred (2011). Lexicon-based methods for sentiment analysis. Computational linguistics, 37(2), 267—307
  17. Paltoglou, Georgios, Thelwall, Mike (2012). Twitter, MySpace, Digg: Unsupervised sentiment analysis in social media. ACM Transactions on Intelligent Systems and Technology (TIST), 3(4), 66
  18. Feldman, Ronen (2013). Techniques and applications for sentiment analysis. Communications of the ACM, 56(4), 82—89
  19. Ranganath, Rajesh, Jurafsky, Dan, McFarland, Daniel A (2013). Detecting friendly, flirtatious, awkward, and assertive speech in speed-dates. Computer Speech \& Language, 27(1), 89—115
  20. Cataldi, Mario, Ballatore, Andrea, Tiddi, Ilaria, Aufaure, Marie-Aude (2013). Good location, terrible food: detecting feature sentiment in user-generated reviews. Social Network Analysis and Mining, 3(4), 1149—1163
  21. Medhat, Walaa, Hassan, Ahmed, Korashy, Hoda (2014). Sentiment analysis algorithms and applications: A survey. Ain Shams Engineering Journal, 5(4), 1093—1113
  22. Dos Santos, C{\’\i}cero Nogueira, Gatti, Maira (2014). Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts.. , (), 69—78
  23. Li, Bin, Hoi, Steven CH (2014). Online portfolio selection: A survey. ACM Computing Surveys (CSUR), 46(3), 35
  24. Severyn, Aliaksei, Moschitti, Alessandro (2015). Twitter sentiment analysis with deep convolutional neural networks. , (), 959—962
  25. Ding, Xiao, Zhang, Yue, Liu, Ting, Duan, Junwen (2015). Deep Learning for Event-Driven Stock Prediction.. , (), 2327—2333
  26. Kumar, B Shravan, Ravi, Vadlamani (2016). A survey of the applications of text mining in financial domain. Knowledge-Based Systems, 114(), 128—147
  27. Chen, Huimin, Sun, Maosong, Tu, Cunchao, Lin, Yankai, Liu, Zhiyuan (2016). Neural Sentiment Classification with User and Product Attention. , (), 1650—1659
  28. Sahu, Ishan, Majumdar, Debapriyo (2017). Detecting Factual and Non-Factual Content in News Articles. , (), 17


  1. Vinodhini, G, Chandrasekaran, RM (2012). Sentiment analysis and opinion mining: a survey. International Journal, 2(6), 282—292
  2. Smailovi{\’c}, Jasmina, Gr{\v{c}}ar, Miha, Lavra{\v{c}}, Nada, {\v{Z}}nidar{\v{s}}i{\v{c}}, Martin (2013). Predictive sentiment analysis of tweets: A stock market application. , (), 77—88
  3. Day, Min-Yuh, Lee, Chia-Chou (2016). Deep learning for financial sentiment analysis on finance news providers. , (), 1127—1134
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