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Proceedings ArticleDOI

Our Twitter Profiles, Our Selves: Predicting Personality with Twitter

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 media

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Proceedings ArticleDOI

Inferring the demographics of search users: social data meets search queries

TL;DR: It is shown that it is indeed feasible to infer important demographic data of users from their query history based on labelled Likes data and it is believed that this approach could provide valuable information for personalization and monetization even in the absence of demographic data.
Journal ArticleDOI

Predicting user personality by mining social interactions in Facebook

TL;DR: TP2010, a Facebook application, is developed with the goal of inferring personality from the analysis of user interactions within social networks, and the results show that the classifiers have a high level of accuracy, making the proposed approach a reliable method for predicting the user personality.
Journal ArticleDOI

Predicting user behavior in electronic markets based on personality-mining in large online social networks

TL;DR: A personality-based product recommender (PBPR) framework to analyze social media data in order to predict a user’s personality and to subsequently derive its personality- based product preferences is proposed.
Journal ArticleDOI

Predicting Active Users' Personality Based on Micro-Blogging Behaviors

TL;DR: This paper proposed to predict active users' personality traits through micro-blogging behaviors, and indicated that active users's personality traits could be predicted by micro- bloggers' behaviors.
Journal ArticleDOI

Predicting personality from network-based resting-state functional connectivity

TL;DR: RSFC within networks representing social, affective, mnemonic, and executive systems significantly predicted self-reported levels of Extraversion, Neuroticism, Agreeableness, and Openness, providing new insights into the neurobiology of personality.
References
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Book

Data Mining

Ian Witten
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.

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

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 ☆

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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