PhD in Computer Science

Models of collective mood: applications to financial market prediction

Academic year 2012/2013

Sommario del corso

• Program
• Notes
• Teaching tools

Program

Hundreds of millions of individuals now subscribe to online social networking services which function as a medium for the exchange of personal as well as public information. Advances in natural language processing now allow us to tap into that reservoir of psycho-social data, and perform computational social science in realtime. In this presentation I will provide an overview of existing text analysis approaches that have been used to extract indicators of social opinion and sentiment from social media data. Researchers have used these techniques to gauge "national happiness" as well as consumer sentiment towards particular brands and products.  Perhaps most tantalizing, evidence has been found that social media feeds may contain predictive information with regards to a variety of socio-economic phenomena, such as movie box office receipts, product adoption rates, elections, and even stock market fluctuations. With respect to the latter, I will outline our own research on the subject of stock market prediction. My team and I have analyzed large-scale Twitter data to assess daily fluctuations of the public's mood state. We found that these fluctuations contain predictive information with regards to up and down movements of broad market indices, such as the Dow Jones Industrial Average. In other research, we have demonstrated the assortative nature of online sentiment by comparing the mood states of individual users over time to their social network neighbors. My presentation will conclude with an overview of a research project that we are presently involved in to predict adverse societal events from social networking markers.

Class schedule

Note

BIO: Johan Bollen is an associate professor at the Indiana University School of Informatics and Computing.

He was formerly a staff scientist at the Los Alamos National Laboratory (2005-2009) and an Assistant Professor at the Department of Computer Science of Old Dominion University (2002 to 2005). He obtained his PhD in Psychology from the Vrije Universiteit Brussel in 2001.  He has published approximately 70 peer-reviewed papers on problems in web science, social media analytics, sentiment tracking, digital libraries, informetrics, and computational social science. His research has been funded by the Andrew W. Mellon Foundation, National Science Foundation, Library of Congress, National Aeronautics and Space Administration, IARPA, and the Los Alamos National Laboratory. He has taught courses on informatics, web and data mining, information retrieval  and digital libraries, and supervised numerous graduate and PhD students.

• Teaching materials
• Exams and finals
• Go to Moodle
• Visit the forums