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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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Posted Content

EmoDNN: Understanding emotions from short texts through a deep neural network ensemble.

TL;DR: In this paper, a novel ensemble classifier equipped with dynamic dropout convnets is proposed to extract emotions from textual context, and the outcome vectors in a novel embedding model are collectively assembled by lexicon inductions to foster emotion-pertinent features.
Dissertation

Local and social recommendation in decentralized architectures

TL;DR: This thesis proposes an evolution of trust-based recommender systems adapted to decentralized architectures that can be deployed on top of existing social networks, and proposes several heuristics that take into account peer-to-peer constraints, especially regarding network flooding.
Proceedings Article

Using Twitter Data to Infer Personal Values of Japanese Consumers

Yinjun Hu, +1 more
TL;DR: The experiment results show that personal values can be inferred from Twitter data, and the approach based on Bayesian network performs well with skewed training data.
Journal ArticleDOI

A psychologically-inspired fuzzy-based approach for user personality prediction in rumor propagation across social networks

TL;DR: This study ratifies the truth that the personality traits of individuals play a significant role in rumor dissemination and the experimental results prove that users exhibiting a high degree of agreeableness trait are more engaged in rumor sharing activities and the users high in extraversion and openness trait restrain themselves from rumor propagation.
Journal ArticleDOI

Redes Sociales y Personalidad

TL;DR: In this article, a revision teorica pretende recopilar and presentar los resultados of las investigaciones mas actuales en materia de perfilacion indirecta de personalidad, con el fin of encontrar patrones that demuestren la utilidad de determinar the rasgos de personal identity of individuos participantes in un crimen (sean victimas o autores).
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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