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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

Contextualized Multidimensional Personality Recognition using Combination of Deep Neural Network and Ensemble Learning

TL;DR: The proposed method was validated on the Essay and YouTube datasets by conducting a series of experiments and the empirical results demonstrated the superiority of the proposed method on both datasets compared to both machine learning and deep learning methods for the task of personality recognition.
Proceedings ArticleDOI

Personalized presentation builder

TL;DR: This paper is an attempt to introduce the Storytelling System which is a subcomponent of the Narrative Visualization Recommender System and go through its conceptual design which allows to share personalized story with other users and find an acceptable model to measure the effectiveness of such a system as a means of information presentation.
Journal ArticleDOI

New Approach of Measuring Human Personality Traits Using Ontology-Based Model from Social Media Data

TL;DR: In this article, a Big Five personality trait-based model was developed to detect human personalities from their textual data in the Indonesian language. And the model uses an ontology approach instead of the more famous machine learning model.

Using weak supervision to scale the development of machine-learning models for social media-based marketing research

TL;DR: It is proposed that the organic structure of social media itself can be leveraged to circumvent the need for curated training data for a variety of marketingrelevant prediction and classification tasks, making such models much more accessible and useful to marketers.
Journal ArticleDOI

Behaviour Analysis Voting Model Using Social Media Data

TL;DR: A proposed model that shows how classification techniques can be used to recognize the personality according to the individuals' tweets using voting technique to enhance the accuracy of every approach individually on the dataset is presented.
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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