Jason Rentfrow is Reader in Personality and Individual Differences in the Department of Psychology at the University of Cambridge. He is also a Fellow of Fitzwilliam College. His research concerns person-environment interactions and focuses on the ways in which personality is expressed in everything from people's preferences for music to the places in which they live. A related interest concerns the development of new methods for studying behavioural manifestations of personality, including the use of online social media and mobile sensors.
His research has been published in international peer-reviewed journals, presented at international scientific conferences, and featured in radio, television, and print media, including BBC, NPR, CNN, The New York Times, Los Angeles Times, Sunday Times, The Economist, Boston Globe, Washington Post, Psychology Today, and Science. He has also worked as a consultant and scientific advisor for several organisations, including the BBC and EMI Music, as well as as tech start-ups, including Emotech and Neener.
Data from mobile sensors and online social media are among the most prominent sources of information about human activity. Therefore, efforts to understand the psychological information that such data can reveal will have significant implications for politics, economics, healthcare, and industry. To that end, Jason's aims as a Turing Fellow are to establish collaborations with researchers from different disciplines to work on research concerned with evaluating the validity of mobile sensor data and online social media data for making predictions about the psychological characteristics of users.
Given the Institute's strong focus on machine learning, one of his goals is to focus on research concerned with the types of psychological information that can be gleaned from mobile sensor data. Using mobile sensor data for several thousand users, one question that he plan to examine is whether valid information about personality or mood can be inferred from the behavioural and contextual data gathered from mobile sensors.
Another goal is to focus on how social media data can be used to measure the psychological characteristics of places. Places vary considerably on a range of important political, economic, social, and health outcomes. However, a limitation of most geographical research in this area is that the spatial resolution of the data is rather course, making it hard to obtain reliable estimates at a fine-grain level of analysis (e.g., neighbourhoods). Online social media (e.g., Twitter, Flickr) as well as data from Google Street View has the potential to overcome that limitation.