Recent Research Publications
Wang, N., Kosinski, M., Stillwell, D.J. & Rust, J. (2012) Can
well-being be measured using Facebook status updates? Validation of
Facebook’s Gross National Happiness Index. Social Indicators
Research.
Abstract
Facebook's Gross National Happiness (FGNH) indexes the positive and negative words used in the millions of status updates submitted daily by Facebook users. FGNH has face validity: it shows a weekly cycle and increases on national holidays. Also, happier individuals use more positive words and fewer negative words in their status updates (Kramer, 2010). We examined the validity of FGNH in measuring mood and well-being by comparing it with scores on Diener's Satisfaction with Life Scale (SWLS), administered to an average of 34 Facebook users every day for a year, then aggregated by day, week, month, quarter and half year. FGNH and SWLS were not significantly correlated, with a negative correlation coefficient. Also, aggregated SWLS scores showed a positive relationship with numbers of negative words in status updates. We conclude that FGNH is a valid measure for neither mood nor well-being; however, it may play a role in mood regulation. This challenges the assumption that linguistic analysis of internet messages is related to underlying psychological states.
[Link to article]
Stillwell, D.J. & Tunney, R.J. (2012) Effects of measurement
methods on the relationship between smoking and delay reward
discounting. Addiction.
Abstract
Aims: Delay reward discounting (DRD) measures the degree to which a person prefers smaller rewards soon or larger rewards later. People who smoke have been shown to have higher DRD. There are several ways of measuring DRD and the method used might influence the association between smoking and DRD. The key differences are the order that the items are presented in, the delays used, and the magnitude of the delayed amount.
Setting: An international online study running from September 2010 to June 2011.
Participants: N = 9454; 38% male, mean age = 23.1.
Design and Measurements: Users completed a multi-item DRD task. They were randomly presented the immediate rewards in an ascending, descending, or randomized order. The delays were between 1 week and 5 years. The delayed amounts were $1000 for all delays, and $100 for 1 month. Users also self-reported their smoking status.
Findings: A hyperbolic DRD function fit better than an exponential function. There were differences in the derived DRD function based on methodology used. Items presented in a randomized order, longer delays and smaller rewards showed steeper discounting. However, these did not interact with smoking status, as for all methodologies used daily smokers showed the steepest discounting, followed by non-daily smokers, then non-smokers.
Conclusions: Smokers discount more steeply irrespective of which method is used. However, the methods of assessing DRD influence the parameters, which means that parameters estimated with different methods cannot be compared.
[Link
to article]
Quercia, D., Lambiotte, R., Kosinski, M., Stillwell, D. & Crowcroft, J. (2011) The Personality of Popular Facebook Users. ACM CSCW 2012.
Abstract
We study the relationship between Facebook popularity (number of contacts) and personality traits on a large number of subjects. We test to which extent two prevalent viewpoints hold. That is, popular users (those with many social contacts) are the ones whose personality traits either predict many offline (real world) friends or predict propensity to maintain superficial relationships. We find that the predictor for number of friends in the real world (Extraversion) is also a predictor for number of Facebook contacts. We then test whether people who have many social contacts on Facebook are the ones who are able to adapt themselves to new forms of communication, present themselves in likable ways, and have propensity to maintain superficial relationships. We show that there is no statistical evidence to support such a conjecture.
[Link
to article]
Quercia, D., Kosinski, M., Stillwell, D. & Crowcroft, J. (2011)
Our Twitter profiles, our selves: Predicting personality with Twitter. IEEE SocialCom.
Abstract
Psychological personality has been shown to affect a variety of aspects: preferences for interaction styles in the digital world and for music genres, for example. Consequently, the design of personalized user interfaces and music recommender systems might benefit from understanding the relationship between personality and use of social media. Since there has not been a study between personality and use of Twitter at large, we set out to analyze the relationship between personality and different types of Twitter users, including popular users and influentials. For 335 users, we gather personality data, analyze it, and find that both popular users and influentials are extroverts and emotionally stable (low in the trait of Neuroticism). Interestingly, we also find that popular users are ‘imaginative’ (high in Openness), while influentials tend to be ‘organized’ (high in Conscientiousness). We then show a way of accurately predicting a user’s personality simply based on three counts publicly available on profiles: following, followers, and listed counts. Knowing these three quantities about an active user, one can predict the user’s five personality traits with a rootmean- squared error below 0.88 on a [1; 5] scale. Based on these promising results, we argue that being able to predict user personality goes well beyond our initial goal of informing the design of new personalized applications as it, for example, expands current studies on privacy in social media.