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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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Proceedings ArticleDOI

Predicting facebook-users' personality based on status and linguistic features via flexible regression analysis techniques

TL;DR: This paper explores the use of Linear Regression and Support Vector Regression for predicting the Big Five Personality scores, which provide a quantitative measure of the personality traits of users and finds that SVR with Polynomial and Radial Basis Function kernel, respectively, provides better results in predicting big five personality traits.
Posted Content

Tales of Two Cities: Using Social Media to Understand Idiosyncratic Lifestyles in Distinctive Metropolitan Areas

TL;DR: In this article, the authors examined and compared lifestyle behaviors of people living in cities of different sizes, utilizing freely available social media data as a large-scale, low-cost alternative to traditional survey methods.
Book ChapterDOI

On Predicting Geolocation of Tweets Using Convolutional Neural Networks

TL;DR: In this paper, the authors present a new method to predict a Twitter user's location based on the information in a single tweet, integrating text and user profile meta-data into a single model using a convolutional neural network.
Journal ArticleDOI

T-PCCE: Twitter Personality based Communicative Communities Extraction System for Big Data

TL;DR: This work describes the Twitter Personality based Communicative Communities Extraction (T-PCCE) system that identifies the most communicative communities in a Twitter network graph considering users’ personality, and defines several metrics to count the strength of communication within each community.
Journal ArticleDOI

Predicting Personality from Social Media Text

TL;DR: Preliminary analysis suggests relative scores between groups of subjects may be maintained, which may be sufficient for many applications, and Mean Absolute Error rates in the 15–30% range, which is a higher error rate than other personality prediction algorithms in the literature.
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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