Book ChapterDOI
Personality Prediction of Social Network Users Using Ensemble and XGBoost
Aditi V. Kunte,Suja S. Panicker +1 more
- pp 133-140
TLDR
Predicting personality using social media is a new approach where direct interaction with people can be eliminated and accurate predictions can be built and high accuracy of 82.59% with an Ensemble is indicated.Abstract:
Machine learning has gained tremendous attention from researchers recently. It has wide applications in tasks such as prediction and classification. Current work focuses on the effective detection of the personality of social network users. Personality is a combination of one’s thinking and behavior. Having knowledge about personality of a person has many applications in real world such as varied recommendation systems or HR departments. Personality of a person can be better understood by interacting with him/her. Predicting personality using social media is a new approach where direct interaction with people can be eliminated and accurate predictions can be built. Although different machine learning methods have been used by researchers recently for the task of prediction, the use of Ensembles has not been explored. Current work focuses on advanced classifiers such as XGBoost and Ensemble for prediction. Experimentation on the real-time Twitter dataset indicates high accuracy of 82.59% with an Ensemble. These results are encouraging for future research.read more
References
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Journal ArticleDOI
Predicting the Big 5 personality traits from digital footprints on social media: A meta-analysis
TL;DR: Results show that the predictive power of digital footprints over personality traits is in line with the standard “correlational upper-limit” for behavior to predict personality, with correlations ranging from 0.29 (Agreeableness) to 0.40 (Extraversion).
Journal ArticleDOI
Computational personality recognition in social media
Golnoosh Farnadi,Geetha Sitaraman,Shanu Sushmita,Fabio Celli,Michal Kosinski,David Stillwell,Sergio Davalos,Marie-Francine Moens,Martine De Cock +8 more
TL;DR: A comparative analysis of state-of-the-art computational personality recognition methods on a varied set of social media ground truth data from Facebook, Twitter and YouTube is performed.
Journal ArticleDOI
Personality Prediction System from Facebook Users
TL;DR: This study attempts to build a system that can predict a person’s personality based on Facebook user information by implementing some deep learning architectures and succeeds to outperform the accuracy of previous similar research.
Journal ArticleDOI
Detection of suicide-related posts in Twitter data streams
TL;DR: A new approach that uses the social media platform Twitter to quantify suicide warning signs for individuals and to detect posts containing suicide-related content and the application of the martingale framework highlights changes in online behavior and shows promise for detecting behavioral changes in at-risk individuals.
Journal ArticleDOI
The impact of personality traits on users information-seeking behavior
TL;DR: The impact of the Big Five personality traits on human online information seeking is explored and individuals high in conscientiousness performed fastest in most information-seeking tasks, followed by those high in agreeableness and extraversion.
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