A Web Interface for Analyzing Hate Speech

Lazaros Vrysis, Nikolaos Vryzas, Rigas Kotsakis, Theodora Saridou, Maria Matsiola, Andreas Veglis, Carlos Arcila-Calderón and Charalampos Dimoulas
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Lazaros Vrysis: School of Journalism & Mass Communication, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Nikolaos Vryzas: School of Journalism & Mass Communication, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Rigas Kotsakis: School of Journalism & Mass Communication, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Theodora Saridou: School of Journalism & Mass Communication, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Maria Matsiola: School of Journalism & Mass Communication, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Andreas Veglis: School of Journalism & Mass Communication, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Carlos Arcila-Calderón: Facultad de Ciencias Sociales, Campus Unamuno, University of Salamanca, 37007 Salamanca, Spain
Charalampos Dimoulas: School of Journalism & Mass Communication, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

Future Internet, 2021, vol. 13, issue 3, 1-18

Abstract: Social media services make it possible for an increasing number of people to express their opinion publicly. In this context, large amounts of hateful comments are published daily. The PHARM project aims at monitoring and modeling hate speech against refugees and migrants in Greece, Italy, and Spain. In this direction, a web interface for the creation and the query of a multi-source database containing hate speech-related content is implemented and evaluated. The selected sources include Twitter, YouTube, and Facebook comments and posts, as well as comments and articles from a selected list of websites. The interface allows users to search in the existing database, scrape social media using keywords, annotate records through a dedicated platform and contribute new content to the database. Furthermore, the functionality for hate speech detection and sentiment analysis of texts is provided, making use of novel methods and machine learning models. The interface can be accessed online with a graphical user interface compatible with modern internet browsers. For the evaluation of the interface, a multifactor questionnaire was formulated, targeting to record the users’ opinions about the web interface and the corresponding functionality.

Keywords: hate speech detection; natural language processing; web interface; database; machine learning; lexicon; sentiment analysis; news semantics (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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