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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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Using Social Media Mining for Estimating Theory of Planned Behaviour Parameters.

TL;DR: This position paper presents the scenario of making interventions for increasing the classical music concert-going behaviour of end users and develops a machine learning algorithm that will extract the user model parameters unobtrusively from the micro-blogs of the users.
Journal ArticleDOI

We Can Do That? Technological Advances in Interest Assessment:

TL;DR: In this paper, the authors review five technological advances that currently exist and present how they can be incorporated into our conduct-of-interest assessment and how to use them in our inte...
Journal ArticleDOI

Predicting Mental Health From Followed Accounts on Twitter

TL;DR: This paper examined the extent to which the accounts a user follows on Twitter can be used to predict individual differences in self-reported anxiety, depression, post-traumatic stress, and anger.

AI and consumers manipulation: what the role of EU fair marketing law?

TL;DR: In this paper, two ways in which the employment of AI can lead to distortive results in consumers' decision-making are explained. And some reflections are proposed over the role of fair marketing law in protecting consumers, notably on how EU fair marketing should change in response to the spread of AI-mediated commercial practices.
Journal ArticleDOI

Social Media and Microblogs Credibility: Identification, Theory Driven Framework, and Recommendation

TL;DR: In this paper, a framework for automatic credibility assessment of microblogs is proposed, which combines feature-based and graph-based approaches to identify comprehensive and necessary credibility constructs, and the framework is also proposed based on the identified constructs.
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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