IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v11y2024i1d10.1057_s41599-024-03899-1.html
   My bibliography  Save this article

From online hate speech to offline hate crime: the role of inflammatory language in forecasting violence against migrant and LGBT communities

Author

Listed:
  • Carlos Arcila Calderón

    (University of Salamanca)

  • Patricia Sánchez Holgado

    (University of Salamanca)

  • Jesús Gómez

    (Secretary of State for Security, Ministry of Interior)

  • Marcos Barbosa

    (University of Salamanca)

  • Haodong Qi

    (Malmö University)

  • Alberto Matilla

    (Secretary of State for Security, Ministry of Interior)

  • Pilar Amado

    (Secretary of State for Security, Ministry of Interior)

  • Alejandro Guzmán

    (Universidad Autónoma de Madrid)

  • Daniel López-Matías

    (Universidad Rey Juan Carlos)

  • Tomás Fernández-Villazala

    (Secretary of State for Security, Ministry of Interior)

Abstract

Social media messages often provide insights into offline behaviors. Although hate speech proliferates rapidly across social media platforms, it is rarely recognized as a cybercrime, even when it may be linked to offline hate crimes that typically involve physical violence. This paper aims to anticipate violent acts by analyzing online hate speech (hatred, toxicity, and sentiment) and comparing it to offline hate crime. The dataset for this preregistered study included social media posts from X (previously called Twitter) and Facebook and internal police records of hate crimes reported in Spain between 2016 and 2018. After conducting preliminary data analysis to check the moderate temporal correlation, we used time series analysis to develop computational models (VAR, GLMNet, and XGBTree) to predict four time periods of these rare events on a daily and weekly basis. Forty-eight models were run to forecast two types of offline hate crimes, those against migrants and those against the LGBT community. The best model for migrant crime achieved an R2 of 64%, while that for LGBT crime reached 53%. According to the best ML models, the weekly aggregations outperformed the daily aggregations, the national models outperformed those geolocated in Madrid, and those about migration were more effective than those about LGBT people. Moreover, toxic language outperformed hatred and sentiment analysis, Facebook posts were better predictors than tweets, and in most cases, speech temporally preceded crime. Although we do not make any claims about causation, we conclude that online inflammatory language could be a leading indicator for detecting potential hate crimes acts and that these models can have practical applications for preventing these crimes.

Suggested Citation

  • Carlos Arcila Calderón & Patricia Sánchez Holgado & Jesús Gómez & Marcos Barbosa & Haodong Qi & Alberto Matilla & Pilar Amado & Alejandro Guzmán & Daniel López-Matías & Tomás Fernández-Villazala, 2024. "From online hate speech to offline hate crime: the role of inflammatory language in forecasting violence against migrant and LGBT communities," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
  • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03899-1
    DOI: 10.1057/s41599-024-03899-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-024-03899-1
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41599-024-03899-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Machin, Stephen & Ivandic, Ria & Kirchmaier, Tom, 2019. "Jihadi Attacks, Media and Local Hate Crime," CEPR Discussion Papers 13743, C.E.P.R. Discussion Papers.
    2. Sebastian Wachs & Michelle F. Wright & Ruthaychonnee Sittichai & Ritu Singh & Ramakrishna Biswal & Eun-mee Kim & Soeun Yang & Manuel Gámez-Guadix & Carmen Almendros & Katerina Flora & Vassiliki Daskal, 2019. "Associations between Witnessing and Perpetrating Online Hate in Eight Countries: The Buffering Effects of Problem-Focused Coping," IJERPH, MDPI, vol. 16(20), pages 1-13, October.
    3. Daniel Devine, 2021. "Discrete Events and Hate Crimes: The Causal Role of the Brexit Referendum," Social Science Quarterly, Southwestern Social Science Association, vol. 102(1), pages 374-386, January.
    4. 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.
    5. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    6. Karsten Müller & Carlo Schwarz, 2023. "From Hashtag to Hate Crime: Twitter and Antiminority Sentiment," American Economic Journal: Applied Economics, American Economic Association, vol. 15(3), pages 270-312, July.
    7. Sylwia J Piatkowska & Brendan Lantz, 2021. "Temporal Clustering of Hate Crimes in the Aftermath of the Brexit Vote and Terrorist Attacks: A Comparison of Scotland and England and Wales [‘Psychological reactions to the 2017 Manchester Arena B," The British Journal of Criminology, Centre for Crime and Justice Studies, vol. 61(3), pages 648-669.
    8. Karsten Müller & Carlo Schwarz, 2021. "Fanning the Flames of Hate: Social Media and Hate Crime [Radio and the Rise of The Nazis in Prewar Germany]," Journal of the European Economic Association, European Economic Association, vol. 19(4), pages 2131-2167.
    9. 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.
    10. Alexander L. Janus, 2010. "The Influence of Social Desirability Pressures on Expressed Immigration Attitudes," Social Science Quarterly, Southwestern Social Science Association, vol. 91(4), pages 928-946, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. CARR, Joel, 2022. "BLM protests and racial hate crime in the United States," Working Papers 2022008, University of Antwerp, Faculty of Business and Economics.
    2. Carlos Arcila-Calderón & David Blanco-Herrero & Maximiliano Frías-Vázquez & Francisco Seoane-Pérez, 2021. "Refugees Welcome? Online Hate Speech and Sentiments in Twitter in Spain during the Reception of the Boat Aquarius," Sustainability, MDPI, vol. 13(5), pages 1-16, March.
    3. Ma, Jie & Tse, Ying Kei & Wang, Xiaojun & Zhang, Minhao, 2019. "Examining customer perception and behaviour through social media research – An empirical study of the United Airlines overbooking crisis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 192-205.
    4. Tähtinen, Tuuli, 2024. "When Facebook Is the Internet: The Role of Social Media in Ethnic Conflict," World Development, Elsevier, vol. 180(C).
    5. Müller-Hansen, Finn & Lee, Yuan Ting & Callaghan, Max & Jankin, Slava & Minx, Jan C., 2022. "The German coal debate on Twitter: Reactions to a corporate policy process," Energy Policy, Elsevier, vol. 169(C).
    6. Daesik Kim & Chung Joo Chung & Kihong Eom, 2022. "Measuring Online Public Opinion for Decision Making: Application of Deep Learning on Political Context," Sustainability, MDPI, vol. 14(7), pages 1-16, March.
    7. Gabriele Ranco & Ilaria Bordino & Giacomo Bormetti & Guido Caldarelli & Fabrizio Lillo & Michele Treccani, 2014. "Coupling news sentiment with web browsing data improves prediction of intra-day price dynamics," Papers 1412.3948, arXiv.org, revised Dec 2015.
    8. Tadić, Bosiljka & Mitrović Dankulov, Marija & Melnik, Roderick, 2023. "Evolving cycles and self-organised criticality in social dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    9. Ping-Yu Hsu & Hong-Tsuen Lei & Shih-Hsiang Huang & Teng Hao Liao & Yao-Chung Lo & Chin-Chun Lo, 2019. "Effects of sentiment on recommendations in social network," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 253-262, June.
    10. Cohen, Scott & Stienmetz, Jason & Hanna, Paul & Humbracht, Michael & Hopkins, Debbie, 2020. "Shadowcasting tourism knowledge through media: Self-driving sex cars?," Annals of Tourism Research, Elsevier, vol. 85(C).
    11. Zhang, Xuetong & Zhang, Weiguo, 2023. "Information asymmetry, sentiment interactions, and asset price," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    12. Indy Wijngaards & Martijn Burger & Job van Exel, 2019. "The promise of open survey questions—The validation of text-based job satisfaction measures," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-22, December.
    13. Junegak Joung & Ki-Hun Kim & Kwangsoo Kim, 2021. "Data-Driven Approach to Dual Service Failure Monitoring From Negative Online Reviews: Managerial Perspective," SAGE Open, , vol. 11(1), pages 21582440209, January.
    14. Ema Kušen & Mark Strembeck, 2021. "“Evacuate everyone south of that line” Analyzing structural communication patterns during natural disasters," Journal of Computational Social Science, Springer, vol. 4(2), pages 531-565, November.
    15. Wen Zhang & Daniel R. Fesenmaier, 2018. "Assessing emotions in online stories: comparing self-report and text-based approaches," Information Technology & Tourism, Springer, vol. 20(1), pages 83-95, December.
    16. Sejung Park & Jin-A Choi, 2023. "Comparing public responses to apologies: examining crisis communication strategies using network analysis and topic modeling," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3603-3620, August.
    17. Simon Albrecht & Bernhard Lutz & Dirk Neumann, 2020. "The behavior of blockchain ventures on Twitter as a determinant for funding success," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(2), pages 241-257, June.
    18. Gisli Gylfason, 2023. "From Tweets to the Streets: Twitter and Extremist Protests in the United States," PSE Working Papers halshs-04188189, HAL.
    19. Jun Lee & Adam Jatowt & Kyoung‐Sook Kim, 2021. "Discovering underlying sensations of human emotions based on social media," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(4), pages 417-432, April.
    20. Sergey Smetanin, 2022. "Pulse of the Nation: Observable Subjective Well-Being in Russia Inferred from Social Network Odnoklassniki," Mathematics, MDPI, vol. 10(16), pages 1-38, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03899-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.