Proceedings ArticleDOI
Our Twitter Profiles, Our Selves: Predicting Personality with Twitter
Daniele Quercia,Michal Kosinski,David Stillwell,Jon Crowcroft +3 more
- pp 180-185
TLDR
It is argued that being able to predict user personality goes well beyond the initial goal of informing the design of new personalized applications as it, for example, expands current studies on privacy in social media.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 root-mean-squared error below 088 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 mediaread more
Citations
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Proceedings ArticleDOI
Predicting Personality with Social Behavior
Sibel Adali,Jennifer Golbeck +1 more
TL;DR: A set of measures based on one's behavior towards her friends and followers that perform as well as textual features in determining personality are introduced.
Book ChapterDOI
Personality and Recommender Systems
Marko Tkalcic,Li Chen +1 more
TL;DR: Studies have shown that personality was successful at tackling the cold-start problem, making group recommendations, addressing cross-domain preferences and at generating diverse recommendations, however, a number of challenges still remain.
Proceedings ArticleDOI
Taxonomy of Risks posed by Language Models
Laura Weidinger,Jonathan Uesato,Maribeth Rauh,C. Griffin,Po-Sen Huang,John F. J. Mellor,A. Glaese,M. Cheng,Borja Balle,Atoosa Kasirzadeh,Courtney Biles,Sande Minnich Brown,Zachary Kenton,William T. Hawkins,Thomas Stepleton,Abeba Birhane,Lisa Anne Hendricks,Laura Rimell,William S. Isaac,Julia Haas,Sean Legassick,Geoffrey Irving,Iason Gabriel +22 more
TL;DR: A comprehensive taxonomy of ethical and social risks associated with LMs is developed, drawing on expertise and literature from computer science, linguistics, and the social sciences to ensure that language models are developed responsibly.
Journal ArticleDOI
Personality and location-based social networks
TL;DR: The study concludes that personality traits help to explain individual differences in LBSN usage and the type of places visited, which is surprising for Extroversion.
Proceedings ArticleDOI
Multiple Social Network Learning and Its Application in Volunteerism Tendency Prediction
TL;DR: A novel model for data missing completion is proposed that is applicable to many other domains, such as demographic inference and interest prediction, and a robust multiple social network learning model is developed and applied to the application of volunteerism tendency prediction.
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