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
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References
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Book
Data Mining
TL;DR: In this paper, generalized estimating equations (GEE) with computing using PROC GENMOD in SAS and multilevel analysis of clustered binary data using generalized linear mixed-effects models with PROC LOGISTIC are discussed.
The Big Five Trait taxonomy: History, measurement, and theoretical perspectives.
Oliver P. John,Sanjay Srivastava +1 more
TL;DR: The Big Five taxonomy as discussed by the authors is a taxonomy of personality dimensions derived from analyses of the natural language terms people use to describe themselves 3 and others, and it has been used for personality assessment.
Journal ArticleDOI
Data mining: practical machine learning tools and techniques with Java implementations
Ian H. Witten,Eibe Frank +1 more
TL;DR: This presentation discusses the design and implementation of machine learning algorithms in Java, as well as some of the techniques used to develop and implement these algorithms.
Journal ArticleDOI
The international personality item pool and the future of public-domain personality measures ☆
Lewis R. Goldberg,John A. Johnson,Herbert W. Eber,Robert Hogan,Michael C. Ashton,C. Robert Cloninger,Harrison G. Gough +6 more
TL;DR: The International Personality Item Pool (IPIP) as mentioned in this paper has been used as a prototype for public-domain personality measures, focusing on the International personality item pool, which has been widely used for personality measurement.
Journal ArticleDOI
The longitudinal course of marital quality and stability: A review of theory, methods, and research.
TL;DR: A model is outlined that integrates the strengths of previous theories of marriage, accounts for established findings, and indicates new directions for research on how marriages change.
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