Human Computer Interaction, Artificial Intelligence and Intelligent Augmentation

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Paper Type

Complete

Paper Number

1913

Description

Hate speech in an online environment has detrimental impacts on the wellbeing of individuals, online communities, and social network platforms. Consequently, the automated detection of hate speech have become a significant issue for various stakeholders. While previous studies have proposed many approaches for this issue, we find an important research gap that they have neglected a plethora of studies from psychology investigating the relationship between personality and hate. To fill the gap, we adopt a text-mining approach which fully automates the process of personality inference. Based its results, we build a personality-based deep learning model for detecting online hate speech (i.e., PERSONA). We validated our model with two real-world cases. The results show that our model significantly outperforms state-of-the-art baselines including a method proposed by Google. Our study paves the way for future research by incorporating psychological aspects into the design of a deep-learning model for hate speech detection.

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Dec 14th, 12:00 AM

PERSONA: Personality-Based Deep Learning for Detecting Hate Speech

Hate speech in an online environment has detrimental impacts on the wellbeing of individuals, online communities, and social network platforms. Consequently, the automated detection of hate speech have become a significant issue for various stakeholders. While previous studies have proposed many approaches for this issue, we find an important research gap that they have neglected a plethora of studies from psychology investigating the relationship between personality and hate. To fill the gap, we adopt a text-mining approach which fully automates the process of personality inference. Based its results, we build a personality-based deep learning model for detecting online hate speech (i.e., PERSONA). We validated our model with two real-world cases. The results show that our model significantly outperforms state-of-the-art baselines including a method proposed by Google. Our study paves the way for future research by incorporating psychological aspects into the design of a deep-learning model for hate speech detection.

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