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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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Citations
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Journal ArticleDOI

Using Big Data and Machine Learning in Personality Measurement: Opportunities and Challenges:

TL;DR: It is expected that this paper will provide insights, guidance, and inspiration that helps personality researchers navigate the challenges and opportunities posed by using big data methods in personality measurement.
Proceedings ArticleDOI

Digital footprints: predicting personality from temporal patterns of technology use

TL;DR: This work presents a novel form of digital traces for user modeling: temporal patterns of smartphone and personal computer activity and presents a machine learning method for binary classification of each Big Five personality trait using these temporal activity patterns of both computer and smartphones as model features.
Proceedings ArticleDOI

OLAP of the tweets: From modeling toward exploitation

TL;DR: A generic multidimensional model dedicated to the OLAP of tweets is proposed with some results and analyses for testing this multi-dimensional model on various data extracted from tweets.
Book ChapterDOI

Personality Prediction Based on All Characters of User Social Media Information

TL;DR: This paper conducted a Big-Five personality inventory test with 131 users of Chinese social network Sina Weibo, and crawled all of their Weibo texts and profile information and used machine learning method to successfully predict the Big- five personality of users.
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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