Generalisation of Cyberbullying Detection

被引：2

作者：

Larochelle, Marc-Andre ^{[1
]}

Khoury, Richard ^{[1
]}

机构：

[1] Univ Laval, Comp Sci & Software Engn Dept, Quebec City, PQ, Canada

来源：

2020 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM) | 2020年

关键词：

natural language processing; deep learning; cyberbullying; cross-domain generalisation;

D O I：

10.1109/ASONAM49781.2020.9381476

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Filtering out Cyberbullying of communities has proven to be a challenge, and efforts have led to the creation of many different datasets to train classifiers. Through these datasets, we will explore the variety of definitions of cyberbullying behaviors and the impact of these differences on the portability of one classifier to another community. We also gain insight on the generalization power of these classifiers. A study of ensemble models combining these classifiers will help us understand how they interact with each other.

引用

页码：296 / 300

页数：5

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