@inproceedings{tang-shen-2020-categorizing,
title = "Categorizing Offensive Language in Social Networks: A {C}hinese Corpus, Systems and an Explainable Tool",
author = "Tang, Xiangru and
Shen, Xianjun",
editor = "Sun, Maosong and
Li, Sujian and
Zhang, Yue and
Liu, Yang",
booktitle = "Proceedings of the 19th Chinese National Conference on Computational Linguistics",
month = oct,
year = "2020",
address = "Haikou, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2020.ccl-1.97",
pages = "1045--1056",
abstract = "Recently, more and more data have been generated in the online world, filled with offensive language such as threats, swear words or straightforward insults. It is disgraceful for a progressive society, and then the question arises on how language resources and technologies can cope with this challenge. However, previous work only analyzes the problem as a whole but fails to detect particular types of offensive content in a more fine-grained way, mainly because of the lack of annotated data. In this work, we present a densely annotated data-set COLA",
language = "English",
}
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%0 Conference Proceedings
%T Categorizing Offensive Language in Social Networks: A Chinese Corpus, Systems and an Explainable Tool
%A Tang, Xiangru
%A Shen, Xianjun
%Y Sun, Maosong
%Y Li, Sujian
%Y Zhang, Yue
%Y Liu, Yang
%S Proceedings of the 19th Chinese National Conference on Computational Linguistics
%D 2020
%8 October
%I Chinese Information Processing Society of China
%C Haikou, China
%G English
%F tang-shen-2020-categorizing
%X Recently, more and more data have been generated in the online world, filled with offensive language such as threats, swear words or straightforward insults. It is disgraceful for a progressive society, and then the question arises on how language resources and technologies can cope with this challenge. However, previous work only analyzes the problem as a whole but fails to detect particular types of offensive content in a more fine-grained way, mainly because of the lack of annotated data. In this work, we present a densely annotated data-set COLA
%U https://aclanthology.org/2020.ccl-1.97
%P 1045-1056
Markdown (Informal)
[Categorizing Offensive Language in Social Networks: A Chinese Corpus, Systems and an Explainable Tool](https://aclanthology.org/2020.ccl-1.97) (Tang & Shen, CCL 2020)
ACL