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Open AccessJournal ArticleDOI

Personality Modelling of Indonesian Twitter Users with XGBoost Based on the Five Factor Model

Derwin Suhartono
- 30 Apr 2021 - 
- Vol. 14, Iss: 2, pp 248-261
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This article is published in International Journal of Intelligent Engineering and Systems.The article was published on 2021-04-30 and is currently open access. It has received 4 citations till now. The article focuses on the topics: Personality & Big Five personality traits.

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Citations
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Journal ArticleDOI

Comparison of machine learning algorithms for content based personality resolution of tweets

TL;DR: This study endeavored to build a system that could predict an individual's personality through SM conversation using six supervised machine learning algorithms to handle unstructured and unbalanced SM conversations.
Journal ArticleDOI

The Performance of Personality-based Recommender System for Fashion with Demographic Data-based Personality Prediction

TL;DR: A new method to predict personality implicitly based on demographic data is proposed, based on findings by previous researchers stating that there is a correlation between demographic data and personality trait.
Proceedings ArticleDOI

Scoping natural language processing in Indonesian and Malay for education applications

TL;DR: A wide-ranging overview of Indonesian and Malay human language technologies and corpus work is conducted, concluding that the field was dominated by exploratory corpus work, machine reading of text gathered from the Internet, and sentiment analysis.
References
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Journal ArticleDOI

An introduction to the five-factor model and its applications.

TL;DR: It is argued that the five-factor model of personality should prove useful both for individual assessment and for the elucidation of a number of topics of interest to personality psychologists.
Journal ArticleDOI

Personality and motivations associated with Facebook use

TL;DR: Investigation of how the Five-Factor Model of personality relates to Facebook use indicated that personality factors were not as influential as previous literature would suggest, but a motivation to communicate was influential in terms of Facebook use.
Proceedings Article

Named Entity Recognition in Tweets: An Experimental Study

TL;DR: The novel T-ner system doubles F1 score compared with the Stanford NER system, and leverages the redundancy inherent in tweets to achieve this performance, using LabeledLDA to exploit Freebase dictionaries as a source of distant supervision.
Journal ArticleDOI

Uses and Gratifications of Social Media: A Comparison of Facebook and Instant Messaging:

TL;DR: Comparative work that examines the gratifications obtained from Facebook with those from instant messaging showed that Facebook is about having fun and knowing about the social activities occurring in one’s social network, whereas instant messaging is geared more toward relationship maintenance and development.
Journal ArticleDOI

Social network use and personality

TL;DR: In this study the self-reports of subjects, were replaced by more objective criteria, measurements of the user-information upload on Facebook, and a strong connection was found between personality and Facebook behavior.
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