Selecting and combining complementary feature representations and classifiers for hate speech detection-Reference-Cited by-同舟云学术

Selecting and combining complementary feature representations and classifiers for hate speech detection

Published:2022-03 Issue: Volume:28 Page:100194
ISSN:2468-6964
Container-title:Online Social Networks and Media
language:en
Short-container-title:Online Social Networks and Media

Author:

Cruz Rafael M.O.^ORCID,de Sousa Woshington V.,Cavalcanti George D.C.^ORCID

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Communication,Information Systems

Reference74 articles.

1. R. Batool, W.A. Khan, M. Hussain, J. Maqbool, M. Afzal, S. Lee, Towards personalized health profiling in social network, in: International Conference On New Trends In Information Science, Service Science And Data Mining, 2012, pp. 760–765.

2. Ensemble method for Indonesian Twitter hate speech detection;Fauzi;Indonesian J. Electr. Eng. Comput. Sci.,2018

3. P.N. Howard, B. Kollanyi, S. Woolley, Bots and automation over Twitter during the US election, Computational Propaganda Project: Working Paper Series, 2016.

4. The DARPA Twitter bot challenge;Subrahmanian;Computer,2016

5. Discrimination, depression, and anxiety among college women in the trump era;Daftary;J. Gend. Stud.,2020

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fake news detection: Taxonomy and comparative study;Information Fusion;2024-03

2. Semi-meta-supervised hate speech detection;Knowledge-Based Systems;2024-03

3. Twitter’s pulse on hydrogen energy in 280 characters: a data perspective;Social Network Analysis and Mining;2024-02-01

4. A survey on hate speech detection and sentiment analysis using machine learning and deep learning models;Alexandria Engineering Journal;2023-10

5. Multilingual hate speech detection sentimental analysis on social media platforms using optimal feature extraction and hybrid diagonal gated recurrent neural network;The Journal of Supercomputing;2023-05-30