Predicting Strategic Behavior from Free Text (Extended Abstract)

The connection between messaging and action is fundamental both to web applications, such as web search and sentiment analysis, and to economics. However, while prominent online applications exploit messaging in natural (human) language in order to predict non-strategic action selection, the economics literature focuses on the connection between structured stylized messaging to strategic decisions in games and multi-agent encounters. This paper aims to connect these two strands of research, which we consider highly timely and important due to the vast online textual communication on the web. Particularly, we introduce the following question: can free text expressed in natural language serve for the prediction of action selection in an economic context, modeled as a game? We initiate research on this question by providing preliminary positive results.

[1]  D. Asch,et al.  Facebook language predicts depression in medical records , 2018, Proceedings of the National Academy of Sciences.

[2]  Moshe Tennenholtz,et al.  Psychological Forest: Predicting Human Behavior , 2016, AAAI.

[3]  Vadlamani Ravi,et al.  A survey on opinion mining and sentiment analysis: Tasks, approaches and applications , 2015, Knowl. Based Syst..

[4]  Jordan L. Boyd-Graber,et al.  Linguistic Harbingers of Betrayal: A Case Study on an Online Strategy Game , 2015, ACL.

[5]  Brendan T. O'Connor,et al.  Learning Latent Personas of Film Characters , 2013, ACL.

[6]  Jennifer Golbeck,et al.  Predicting Personality from Twitter , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.

[7]  J. Pennebaker,et al.  The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods , 2010 .

[8]  Panagiotis G. Ipeirotis,et al.  Estimating the Helpfulness and Economic Impact of Product Reviews: Mining Text and Reviewer Characteristics , 2010, IEEE Transactions on Knowledge and Data Engineering.

[9]  Jon Oberlander,et al.  What Are They Blogging About? Personality, Topic and Motivation in Blogs , 2009, ICWSM.

[10]  Moshe Tennenholtz,et al.  Learning in One-Shot Strategic Form Games , 2006, ECML.

[11]  Thorsten Joachims,et al.  Transductive Learning via Spectral Graph Partitioning , 2003, ICML.

[12]  Bo Pang,et al.  Thumbs up? Sentiment Classification using Machine Learning Techniques , 2002, EMNLP.

[13]  Sarit Kraus,et al.  Strategic Negotiation in Multiagent Environments , 2001, Intelligent robots and autonomous agents.

[14]  Thorsten Joachims,et al.  Transductive Inference for Text Classification using Support Vector Machines , 1999, ICML.

[15]  Alexander Gammerman,et al.  Learning by Transduction , 1998, UAI.

[16]  Matthew Rabin,et al.  A Model of Pre-game Communication , 1991 .

[17]  J. Sobel,et al.  STRATEGIC INFORMATION TRANSMISSION , 1982 .

[18]  M. Spence.  Job Market Signaling , 1973 .

[19]  C. Aggarwal.  Opinion Mining and Sentiment Analysis , 2018 .

[20]  Jason S. Hartford,et al.  Deep Learning for Predicting Human Strategic Behavior , 2016, NIPS.

[21]  Douglas Walton,et al.  Argumentation Theory: A Very Short Introduction , 2009, Argumentation in Artificial Intelligence.

[22]  James W. Pennebaker,et al.  Linguistic Inquiry and Word Count (LIWC2007) , 2007 .