Professor Reza Rejaie and Professor Sanjay Srivastava of the Psychology Department have received two grants totaling over $1.1M for their cross-disciplinary research. The over-arching theme of their research is to leverage posted content and relationships of individual users in an online social network (e.g. Twitter and Facebook) to study various aspects of their behavior and personality using data-driven approaches.
The first grant of $375K was awarded from the National Institute for Health (NIH) for research using Twitter to capture and study the impact of a mass shooting event on the population. Their joint research was featured in the article What's in a Tweet? in the Spring issue of CASCADE magazine.
The second grant of $740K was recently awarded by the Directorate for Social, Behavioral & Economic Sciences at the National Science Foundation (NSF) titled "Personality Reputation Formation and Network Structure on Computer Technologies”. The goal of this project is to study how users' personalities and self-presentation goals are reflected in their social media presence, how people form accurate or biased impressions of one another online, and how people make consequential social decisions based on those impressions. The project will also produce important tools for other scientists. By combining the expertise of a personality psychologist with that of a computer scientist, the project will create new methods and techniques for doing large-scale, automated studies in social psychological science and personality psychology. The outcomes of this research will also inform policy discussions on online privacy and on the use of social media in hiring, in spreading news and information online, and other important social and economic transactions.
Srivastava and Rejaie propose to merge "big data" methods from computer science with rigorous laboratory methods from psychology to study personality and reputation on Twitter, a popular online social network with a large and diverse user base in the United States. Five studies focus on a series of related questions about how people convey who they are through Twitter, and how others form impressions by observing such behavior. (1) Data-driven analyses will be used to identify patterns in Twitter users' publicly available information (including profile information, network size and structure, and tweet content) to determine what important stable attributes distinguish users. (2) A sample of Twitter users will complete validated psychometric assessments of personality and self-presentation goals to see how these are reflected in the users' public Twitter data. (3) Research will examine how others form personality impressions based on such Twitter profiles, and the ways those impressions are accurate or biased. (4) Studies will examine how others make important social decisions based on their accurate or inaccurate impressions of Twitter profiles. (5) Finally, research will examine how personality and impressions affect how people decide to affiliate and form online communities. This research will produce new scientific insights about how people express themselves and interact online. It will also generate new tools for assessing personality and reputation in online settings, enabling future "big data" studies in psychology.