Research Article

AUTOMATIC HATE SPEECH DETECTION IN ONLINE CONTENTS USING LATENT SEMANTIC ANALYSIS

Volume: 5 Number: 1 June 30, 2017
  • Xhemal Zenuni
  • Jaumin Ajdari
  • Florije Ismaili
  • Bujar Raufi
EN

AUTOMATIC HATE SPEECH DETECTION IN ONLINE CONTENTS USING LATENT SEMANTIC ANALYSIS

Abstract

Internet in general and social media in particular have greatly facilitated the communication, interaction and collaboration among people and different entities. As generally there is no censorship, these media sometimes are used to proliferate discourses that contain hateful messages targeting ethnic origin, religious or sexual groups, which potentially may degenerate to violent acts against individuals of such groups. Therefore, we explore the idea of building of automatic classifier that can be used for detection of hate speech in public Albanian language pages. A hate speech corpus for Albanian language is created, and then based on Support Vector Machine (SVM) approach,  an automatic hate speech detection system is proposed. Such system can be used to detect and analyze hate speech in online contents over time and to enhance our knowledge on how they affect opinion creation in society.  

Keywords

References

  1. Chen, Y., Zhu, S., Zhou, Y., & Xu, H. (2012). Detecting Offensive Language in Social Media to Protect Adolescent Online Safety. Proceedings of the Fourth ASE/IEEE International Conference on Social Computing. Amsterdam.
  2. Commision, E. (2016). CODE OF CONDUCT ON COUNTERING ILLEGAL HATE SPEECH ONLINE.
  3. Djuric, N., Zhou, J., & Morris, R. (2015). Hate Speech Detection with Comment Embeddings. Proceedings of the 24th International Conference on World Wide Web, (s. 29-30).
  4. Gitari, N., Zuping, Z., Damien, H., & Long, J. (2015). A Lexicon-based Approach for Hate Speech Detection. International Journal of Multimedia and Ubiquitous Engineering, 2015-230. (tarih yok). http://www.rsystems.com/. https://developers.facebook.com/docs/graph-api. (tarih yok).
  5. Joachims, T. (1998). Text Categorization with Support Vector Machines: Learning with Many Relevant Features. European Conference on Machine Learning, (s. 137-142).
  6. Kottasova, I. (2016). Facebook and Twitter pledge to remove hate speech within 24 hours. http://money.cnn.com/2016/05/31/technology/hate-speech-facebook-twitter-eu/.
  7. Kwok, I., & Wang, Y. (2013). Locate the Hate: Detecting Tweets against Blacks. Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, (s. 1621-1622).
  8. Thomas Davidson, D. W. (2017). Automated Hate Speech Detection and the Problem of Offensive Language. In the Proceedings of ICWSM 2017.

Details

Primary Language

English

Subjects

-

Journal Section

Research Article

Authors

Xhemal Zenuni This is me

Jaumin Ajdari This is me

Florije Ismaili This is me

Bujar Raufi This is me

Publication Date

June 30, 2017

Submission Date

February 14, 2017

Acceptance Date

-

Published in Issue

Year 2017 Volume: 5 Number: 1

APA
Zenuni, X., Ajdari, J., Ismaili, F., & Raufi, B. (2017). AUTOMATIC HATE SPEECH DETECTION IN ONLINE CONTENTS USING LATENT SEMANTIC ANALYSIS. PressAcademia Procedia, 5(1), 368-371. https://doi.org/10.17261/Pressacademia.2017.612
AMA
1.Zenuni X, Ajdari J, Ismaili F, Raufi B. AUTOMATIC HATE SPEECH DETECTION IN ONLINE CONTENTS USING LATENT SEMANTIC ANALYSIS. PAP. 2017;5(1):368-371. doi:10.17261/Pressacademia.2017.612
Chicago
Zenuni, Xhemal, Jaumin Ajdari, Florije Ismaili, and Bujar Raufi. 2017. “AUTOMATIC HATE SPEECH DETECTION IN ONLINE CONTENTS USING LATENT SEMANTIC ANALYSIS”. PressAcademia Procedia 5 (1): 368-71. https://doi.org/10.17261/Pressacademia.2017.612.
EndNote
Zenuni X, Ajdari J, Ismaili F, Raufi B (June 1, 2017) AUTOMATIC HATE SPEECH DETECTION IN ONLINE CONTENTS USING LATENT SEMANTIC ANALYSIS. PressAcademia Procedia 5 1 368–371.
IEEE
[1]X. Zenuni, J. Ajdari, F. Ismaili, and B. Raufi, “AUTOMATIC HATE SPEECH DETECTION IN ONLINE CONTENTS USING LATENT SEMANTIC ANALYSIS”, PAP, vol. 5, no. 1, pp. 368–371, June 2017, doi: 10.17261/Pressacademia.2017.612.
ISNAD
Zenuni, Xhemal - Ajdari, Jaumin - Ismaili, Florije - Raufi, Bujar. “AUTOMATIC HATE SPEECH DETECTION IN ONLINE CONTENTS USING LATENT SEMANTIC ANALYSIS”. PressAcademia Procedia 5/1 (June 1, 2017): 368-371. https://doi.org/10.17261/Pressacademia.2017.612.
JAMA
1.Zenuni X, Ajdari J, Ismaili F, Raufi B. AUTOMATIC HATE SPEECH DETECTION IN ONLINE CONTENTS USING LATENT SEMANTIC ANALYSIS. PAP. 2017;5:368–371.
MLA
Zenuni, Xhemal, et al. “AUTOMATIC HATE SPEECH DETECTION IN ONLINE CONTENTS USING LATENT SEMANTIC ANALYSIS”. PressAcademia Procedia, vol. 5, no. 1, June 2017, pp. 368-71, doi:10.17261/Pressacademia.2017.612.
Vancouver
1.Xhemal Zenuni, Jaumin Ajdari, Florije Ismaili, Bujar Raufi. AUTOMATIC HATE SPEECH DETECTION IN ONLINE CONTENTS USING LATENT SEMANTIC ANALYSIS. PAP. 2017 Jun. 1;5(1):368-71. doi:10.17261/Pressacademia.2017.612

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