KBCNMUJAL@HASOC-Dravidian-CodeMix-FIRE20: Using Machine Learning for Detection of Hate Speech and Offensive Code-mixed Social Media

Varsha Pathak*, Manish Joshi, Prasad Joshi, Monica Mundada, Tanmay Joshi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper describes the system submitted by our team, KBCNMUJAL, for Task 2 of the shared task “Hate Speech and Offensive Content Identification in Indo-European Languages (HASOC)” at Forum for Information Retrieval Evaluation, December 16-20, 2020, Hyderabad, India. The datasets of two Dravidian languages viz Malayalam and Tamil of size 4000 observations, each were shared by the HASOC organizers. These datasets are used to train the machine using different machine learning algorithms, based on classification and regression models. The datasets consist of tweets or YouTube comments with two class labels “offensive” and “not offensive”. The machine is trained to classify such social media messages in these two categories. Appropriate n-gram feature sets are extracted to learn the specific characteristics of the Hate Speech text messages. These feature models are based on TFIDF weights of n-gram. The referred work and respective experiments show that the features such as word, character and combined model of word and character n-grams could be used to identify the term patterns of offensive text contents. As a part of the HASOC shared task, the test data sets are made available by the HASOC track organizers. The best performing classification models developed for both languages are applied on test datasets. The model which gives the highest accuracy result on training dataset for Malayalam language was experimented to predict the categories of respective test data. This system has obtained an F1 score of 0.77. Similarly the best performing model for Tamil language has obtained an F1 score of 0.87. This work has received 2nd and 3rd rank in this shared Task 2 for Malayalam and Tamil language respectively. The proposed system is named HASOC_kbcnmujal.
Original languageEnglish
Title of host publicationWorking Notes of FIRE 2020 - Forum for Information Retrieval Evaluation
EditorsParth Mehta, Thomas Mandl, Prasenjit Majumder, Mandar Mitra
Number of pages11
Place of PublicationAachen
PublisherCEUR
Publication date2020
Pages351-361
Publication statusPublished - 2020
EventThe 12th Meeting of Forum for Information Retrieval Evaluation. FIRE 2020 - Virtual Event, Hyderabad, India
Duration: 15 Dec 202020 Dec 2020
Conference number: 12
http://fire.irsi.res.in/fire/2020/home

Workshop

WorkshopThe 12th Meeting of Forum for Information Retrieval Evaluation. FIRE 2020
Number12
LocationVirtual Event
CountryIndia
CityHyderabad
Period15/12/202020/12/2020
Internet address
SeriesCEUR Workshop Proceedings
Volume2826
ISSN1613-0073

Keywords

  • Support vector classifier
  • Multinomial bayes
  • LR
  • Random forest classifier
  • N-gram model
  • Text classifier

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