Anatomy of online hate: Developing a taxonomy and machine learning models for identifying and classifying hate in online news media

Joni Salminen, Hind Almerekhi, Milica Milenković, Soon Gyo Jung, Jisun An, Haewoon Kwak, Bernard Jansen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

Online social media platforms generally attempt to mitigate hateful expressions, as these comments can be detrimental to the health of the community. However, automatically identifying hateful comments can be challenging. We manually label 5,143 hateful expressions posted to YouTube and Facebook videos among a dataset of 137,098 comments from an online news media. We then create a granular taxonomy of different types and targets of online hate and train machine learning models to automatically detect and classify the hateful comments in the full dataset. Our contribution is twofold: 1) creating a granular taxonomy for hateful online comments that includes both types and targets of hateful comments, and 2) experimenting with machine learning, including Logistic Regression, Decision Tree, Random Forest, Adaboost, and Linear SVM, to generate a multiclass, multilabel classification model that automatically detects and categorizes hateful comments in the context of online news media. We find that the best performing model is Linear SVM, with an average F1 score of 0.79 using TF-IDF features. We validate the model by testing its predictive ability, and, relatedly, provide insights on distinct types of hate speech taking place on social media.

Original languageEnglish
Title of host publication12th International AAAI Conference on Web and Social Media, ICWSM 2018
PublisherAAAI press
Pages330-339
Number of pages10
ISBN (Electronic)9781577357988
Publication statusPublished - 1 Jan 2017
Event12th International AAAI Conference on Web and Social Media, ICWSM 2018 - Palo Alto, United States
Duration: 25 Jun 201828 Jun 2018

Other

Other12th International AAAI Conference on Web and Social Media, ICWSM 2018
CountryUnited States
CityPalo Alto
Period25/6/1828/6/18

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Taxonomies
Learning systems
Adaptive boosting
Decision trees
Logistics
Labels
Health
Testing

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Salminen, J., Almerekhi, H., Milenković, M., Jung, S. G., An, J., Kwak, H., & Jansen, B. (2017). Anatomy of online hate: Developing a taxonomy and machine learning models for identifying and classifying hate in online news media. In 12th International AAAI Conference on Web and Social Media, ICWSM 2018 (pp. 330-339). AAAI press.

Anatomy of online hate : Developing a taxonomy and machine learning models for identifying and classifying hate in online news media. / Salminen, Joni; Almerekhi, Hind; Milenković, Milica; Jung, Soon Gyo; An, Jisun; Kwak, Haewoon; Jansen, Bernard.

12th International AAAI Conference on Web and Social Media, ICWSM 2018. AAAI press, 2017. p. 330-339.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Salminen, J, Almerekhi, H, Milenković, M, Jung, SG, An, J, Kwak, H & Jansen, B 2017, Anatomy of online hate: Developing a taxonomy and machine learning models for identifying and classifying hate in online news media. in 12th International AAAI Conference on Web and Social Media, ICWSM 2018. AAAI press, pp. 330-339, 12th International AAAI Conference on Web and Social Media, ICWSM 2018, Palo Alto, United States, 25/6/18.
Salminen J, Almerekhi H, Milenković M, Jung SG, An J, Kwak H et al. Anatomy of online hate: Developing a taxonomy and machine learning models for identifying and classifying hate in online news media. In 12th International AAAI Conference on Web and Social Media, ICWSM 2018. AAAI press. 2017. p. 330-339
Salminen, Joni ; Almerekhi, Hind ; Milenković, Milica ; Jung, Soon Gyo ; An, Jisun ; Kwak, Haewoon ; Jansen, Bernard. / Anatomy of online hate : Developing a taxonomy and machine learning models for identifying and classifying hate in online news media. 12th International AAAI Conference on Web and Social Media, ICWSM 2018. AAAI press, 2017. pp. 330-339
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