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A Web Interface for Analyzing Hate Speech

Author

Listed:
  • 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)

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.

Suggested Citation

  • Lazaros Vrysis & Nikolaos Vryzas & Rigas Kotsakis & Theodora Saridou & Maria Matsiola & Andreas Veglis & Carlos Arcila-Calderón & Charalampos Dimoulas, 2021. "A Web Interface for Analyzing Hate Speech," Future Internet, MDPI, vol. 13(3), pages 1-18, March.
    • Handle: RePEc:gam:jftint:v:13:y:2021:i:3:p:80-:d:522070
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    References listed on IDEAS

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    1. Mike Thelwall & Kevan Buckley & Georgios Paltoglou & Di Cai & Arvid Kappas, 2010. "Sentiment strength detection in short informal text," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2544-2558, December.
    2. de Vries, Erik & Schoonvelde, Martijn & Schumacher, Gijs, 2018. "No Longer Lost in Translation: Evidence that Google Translate Works for Comparative Bag-of-Words Text Applications," Political Analysis, Cambridge University Press, vol. 26(4), pages 417-430, October.
    3. Svenja Boberg & Tim Schatto-Eckrodt & Lena Frischlich & Thorsten Quandt, 2018. "The Moral Gatekeeper? Moderation and Deletion of User-Generated Content in a Leading News Forum," Media and Communication, Cogitatio Press, vol. 6(4), pages 58-69.
    4. María Antonia Paz & Julio Montero-Díaz & Alicia Moreno-Delgado, 2020. "Hate Speech: A Systematized Review," SAGE Open, , vol. 10(4), pages 21582440209, November.
    5. Carlos Arcila Calderón & Gonzalo de la Vega & David Blanco Herrero, 2020. "Topic Modeling and Characterization of Hate Speech against Immigrants on Twitter around the Emergence of a Far-Right Party in Spain," Social Sciences, MDPI, vol. 9(11), pages 1-19, October.
    6. Mike Thelwall & Kevan Buckley & Georgios Paltoglou & Di Cai & Arvid Kappas, 2010. "Sentiment strength detection in short informal text," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2544-2558, December.
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    Cited by:

    1. Nikolaos Vryzas & Anastasia Katsaounidou & Lazaros Vrysis & Rigas Kotsakis & Charalampos Dimoulas, 2022. "A Prototype Web Application to Support Human-Centered Audiovisual Content Authentication and Crowdsourcing," Future Internet, MDPI, vol. 14(3), pages 1-17, February.
    2. Andreas Giannakoulopoulos & Minas Pergantis & Laida Limniati & Alexandros Kouretsis, 2022. "Investigating the Country of Origin and the Role of the .eu TLD in External Trade of European Union Member States," Future Internet, MDPI, vol. 14(6), pages 1-27, June.
    3. Charalampos A. Dimoulas & Andreas Veglis, 2023. "Theory and Applications of Web 3.0 in the Media Sector," Future Internet, MDPI, vol. 15(5), pages 1-10, April.
    4. Paschalia (Lia) Spyridou & Constantinos Djouvas & Dimitra Milioni, 2022. "Modeling and Validating a News Recommender Algorithm in a Mainstream Medium-Sized News Organization: An Experimental Approach," Future Internet, MDPI, vol. 14(10), pages 1-21, September.
    5. Carlos Arcila-Calderón & Javier J. Amores & Patricia Sánchez-Holgado & Lazaros Vrysis & Nikolaos Vryzas & Martín Oller Alonso, 2022. "How to Detect Online Hate towards Migrants and Refugees? Developing and Evaluating a Classifier of Racist and Xenophobic Hate Speech Using Shallow and Deep Learning," Sustainability, MDPI, vol. 14(20), pages 1-16, October.

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