Big Data Techniques to Study the Impact of Gender-Based Violence in the Spanish News Media

Authors

DOI:

https://doi.org/10.51480/1899-5101.16.1(33).6

Keywords:

big data, domestic violence, gender-based violence, media, news

Abstract

Despite being an underreported topic in the news media, gender-based violence (GBV) undermines the health, dignity, security and autonomy of its victims. Research has studied many of the factors that generate or maintain this kind of violence. However, the influence of the media is still uncertain. This paper used Big Data techniques to explore how GBV is depicted and reported in digital news media. By feeding neural networks with news, the topic information associated with each article can be recovered. Our findings show a relationship between GBV news and public awareness, the effect of well-known GBV cases, and the intrinsic thematic relationship of GBV news with justice themes.

Author Biographies

Hugo J. Bello, University of Valladolid

Hugo J. Bello, PhD, is a researcher and teacher at the University of Valladolid, Soria, Spain. His research is focused on applications of machine learning and biostatistics.

Nora Palomar-Ciria, Complejo Asistencial de Soria

Nora Palomar-Ciria, MD, PhD, works as a psychiatrist in a public hospital in Spain (Complejo Asistencial Universitario de Soria). She focus her research in clinical aspects of psychiatry, especially schizophrenia and suicide.

Elisa Gallego, the Carlos III Health Institute in Madrid

Elisa Gallego, MD. She is a specialist in Preventive Medicine and Public Health. She is a researcher at the Research Institute of Rare Diseases of the Carlos III Health Institute, Spain. She works mainly on coding, registration and epidemiology of rare diseases.

Lourdes Jiménez Navascués, University of Valladolid

Lourdes Jiménez Navascués, PhD, RN, is a researcher and lecturer in the Department of Nursing, Faculty of Health Sciences, University of Valladolid, Campus of Soria, Spain. Her topics cover nursing studies, care-related information, well-being in old age and the living conditions of older people and their carers.

Celia Lozano, AI Department in Bosonit

Celia Lozano, PhD, works as a Head of Data & AI in an IT consultant company. She is keen on Artificial Intelligence, Statistical Physics, and Problem Solving.

References

Alexander, J. (2006). The civil sphere (Oxford). Oxford University Press.

Aurrekoetxea, M. (2020). San fermines #la manada case [The San Fermin festival—7–14 July— The Wolfpack case]: An exploratory analysis of social support for victims of sexual violence on Twitter. Computers in Human Behavior, 108, 106299. https://doi.org/10.1016/j.chb.2020.106299

Baker, L., & Ascione, F. (1995). Effects of televised violence on aggression. Journal of Social Issues, 51(3), 85–106.

Bleiker, R., & Hutchison, E. (2019). Gender and violence in news media and photography. In Handbook on Gender and Violence (pp. 231–247). Edward Elgar Publishing. https://www.elgaronline.com/display/edcoll/9781788114684/9781788114684.00023.xml

Boyle, K. (2005). Media and violence: Gendering the debates. Thousand Oaks, Sage.

Buiten, D., & Salo, E. (2007). Silences stifling transformation: Misogyny and gender-based violence in the media. Agenda, 21(71), 115–121. https://doi.org/10.1080/10130950.2007.9674819

Busso, L., Combei, C. R., & Tordini, O. (2020). “Narrating Gender Violence A Corpus-Based Study on the Representation of Gender-Based Violence in Italian Media”. In Giusti, G. & Iannàccaro, G. (Eds) Language, Gender and Hate Speech. A Multidisciplinary Approach, Fondazione Università Ca’ Foscari. https://publications.aston.ac.uk/id/eprint/42283/

Carlyle, K. E., Slater, M. D., & Chakroff, J. L. (2008). Newspaper Coverage of Intimate Partner Violence: Skewing Representations of Risk. The Journal of Communication, 58(1), 168–186. https://doi.org/10.1111/j.1460–2466.2007.00379.x

Chapman, W. W., Nadkarni, P. M., Hirschman, L., D’Avolio, L. W., Savova, G. K., & Uzuner, O. (2011). Overcoming barriers to NLP for clinical text: The role of shared tasks and the need for additional creative solutions. Journal of the American Medical Informatics Association, 18(5), 540–543. https://doi.org/10.1136/amiajnl-2011–000465

Comas-d’Argermir, D. (2015). News of partner feminicides: The shift from private issue to public problem. European Journal of Communication, 30(2), 121–136.

Coppersmith, G., Leary, R., Crutchley, P., & Fine, A. (2018). Natural Language Processing of Social Media as Screening for Suicide Risk. Biomedical Informatics Insights, 10, 1178222618792860. https://doi.org/10.1177/1178222618792860

Cuklanz, L. M. (2014). Mass media representation gendered violence. In The Routledge Companion to Media & Gender. Routledge.

Cullen, P., O’Brien, A., & Corcoran, M. (2019). Reporting on domestic violence in the Irish media: An exploratory study of journalists’ perceptions and practices. Media, Culture & Society, 41(6), 774–790. https://doi.org/10.1177/0163443718823141

DeFleur, M., & Ball-Rokeach, S. (1989). Theories of mass communication (5th ed.). Longman.

Dijk, T. A. van. (1995). Power and the news media: Political Communication and Action. NJ: Hampton Press Cresskill.

Easteal, P., Holland, K., & Judd, K. (2015). Enduring themes and silences in media portrayals of violence against women. Women’s Studies International Forum, 48, 103–113. https://doi.org/10.1016/j.wsif.2014.10.015

Easteal, P., Holland, K., Breen, M. D., Vaughan, C., & Sutherland, G. (2018). Australian Media Messages: Critical Discourse Analysis of Two Intimate Homicides Involving Domestic Violence. Violence Against Women, 1077801218780364. https://doi.org/10.1177/1077801218780364

Egea, M. A. (2019). Subjetividad y violación social. El caso de la manada [Subjectivity and social violation. The ‘wolf pack’ case]. Tropelías: Revista de Teoría de la Literatura y Literatura Comparada, 31, Article 31. https://doi.org/10.26754/ojs_tropelias/tropelias.2019313197

ElSherief, M., Belding, E., & Nguyen, D. (2017). #NotOkay: Understanding Gender-Based Violence in Social Media. Proceedings of the International AAAI Conference on Web and Social Media, 11(1), Article 1. https://doi.org/10.1609/icwsm.v11i1.14877

Farzindar, A., & Inkpen, D. (2017). Natural Language Processing for Social Media: Second Edition. Morgan & Claypool Publishers.

GenderIT (2012). Learning Resource Kit for Gender-Ethical Journalism and Media House Policy. GenderIT.Org https://genderit.org/resources/learning-resource-kit-gender-ethical-journalism-and-media-house-policy

Gillespie, L. K., Richards, T. N., Givens, E. M., & Smith, M. D. (2013). Framing deadly domestic violence: Why the media’s spin matters in newspaper coverage of femicide. Violence Against Women, 19(2), 222–245. https://doi.org/10.1177/1077801213476457

Goldberg, Y. (2017) Neural Network Methods in Natural Language Processing. Morgan and Claypool, Toronto

Heise, L., Ellsberg, M., & Gottmoeller, M. (2002). A global overview of gender-based violence. International Journal of Gynaecology and Obstetrics: The Official Organ of the International Federation of Gynaecology and Obstetrics, 78 Suppl 1, S5–14. https://doi.org/10.1016/S0020–7292(02)00038–3

Heise, L., Greene, M. E., Opper, N., Stavropoulou, M., Harper, C., Nascimento, M., Zewdie, D., & Gender Equality, Norms, and Health Steering Committee. (2019). Gender inequality and restrictive gender norms: Framing the challenges to health. Lancet (London, England), 393(10189), 2440–2454. https://doi.org/10.1016/S0140–6736(19)30652-X

Howe, A. (1997). “The war against women”. Media representations of men’s violence against women in Australia. Violence Against Women, 3(1), 59–75. https://doi.org/10.1177/1077801297003001005

Jewkes, R., Dartnall, E., & Sikweyiya, Y. (2017). Ethical and safety recommendations for research on gender-based violence against women and girls. World Health Organization.

LSE (2020). Artificial intelligence could help protect victims of domestic violence. London School of Economics and Political Science. https://www.lse.ac.uk/News/Latest-news-from-LSE/2020/b-Feb-20/Artificial-intelligence-could-help-protect-victims-of-domestic-violence.aspx

Luengo, M. (2018). Gender violence: The media, civil society, and the struggle for human rights in Argentina. Media, Culture & Society, 40(3), 397–414. https://doi.org/10.1177/0163443717713259

Maydell, E. (2018). ‘It just seemed like your normal domestic violence’: Ethnic stereotypes in print media coverage of child abuse in New Zealand. Media, Culture & Society, 40(5), 707–724. https://doi.org/10.1177/0163443717737610

Menéndez, M. I. (2014). Retos periodísticos ante la violencia de género. El caso de la prensa local en España [Journalistic challenges in the face of gender violence. The case of the local press in Spain]. Nueva Época, 22, 53–77.

Mikolov, T. (2017). Neural Networks for Natural Language Processing. Brno University of Technology, Czechia.

Mills, T. C. (2015). Modelling Stationary Time Series: The ARMA Approach. In T. C. Mills (Ed.), Time Series Econometrics: A Concise Introduction (pp. 5–40). Palgrave Macmillan UK. https://doi.org/10.1057/9781137525338_2

Moorti, S. (2002). The Colour of Rape: Gender and Race in Television’s Public Spheres. State University of New York Press.

Mori, K., & Haruno, M. (2021). Differential ability of network and natural language information on social media to predict interpersonal and mental health traits. Journal of Personality, 89(2), 228–243. https://doi.org/10.1111/jopy.12578

News Desk (2019). ‘Wolf Pack’ verdict overruled: gang receive 15-year sentences. https://www.spainenglish.com/2019/06/21/wolf-pack-verdict-15-year-sentences/

Rollè, L., Santoniccolo, F., D’Amico, D., & Trombetta, T. (2020). News Media Representation of Domestic Violence Victims and Perpetrators: Focus on Gender and Sexual Orientation in International Literature. In S. Ramon, M. Lloyd, & B. Penhale (Eds), Gendered Domestic Violence and Abuse in Popular Culture (pp. 149–169). Emerald Publishing Limited. https://doi.org/10.1108/978–1-83867–781–720201008

Russo, N. F., & Pirlott, A. (2006). Gender-based violence: Concepts, methods, and findings. Annals of the New York Academy of Sciences, 1087, 178–205. https://doi.org/10.1196/annals.1385.024

Shen, J., Valagolam, D., & McCalla, S. (2020). Prophet forecasting model: A machine learning approach to predict the concentration of air pollutants (PM2.5, PM10, O3, NO2, SO2, CO) in Seoul, South Korea. PeerJ, 8, e9961. https://doi.org/10.7717/peerj.9961

Singh, G., Mémoli, F., & Carlsson, G. (2007). Topological Methods for the Analysis of High Dimensional Data Sets and 3D Object Recognition. In Eurographics Symposium on Point-Based Graphics 2007 (p. 100). https://doi.org/10.2312/SPBG/SPBG07/091–100

Subramani, S., Michalska, S., Wang, H., Du, J., Zhang, Y., & Shakeel, M. (2019). Deep Learning for Multi-Class Identification from Domestic Violence Online Posts. IEEE Access, 7, 46210–46224. https://doi.org/10.1109/ACCESS.2019.2908827

Subramani, S., Wang, H., Vu, H. Q., & Li, G. (2018). Domestic Violence Crisis Identification from Facebook Posts Based on Deep Learning. IEEE Access, 6, 54075–54085. https://doi.org/10.1109/ACCESS.2018.2871446

Sutherland, G., Easteal, P., Holland, K., & Vaughan, C. (2019). Mediated representations of violence against women in the mainstream news in Australia. BMC Public Health, 19(1), 502. https://doi.org/10.1186/s12889–019–6793–2

Teruelo, J. G. F. (2011). Feminicidios de género: Evolución real del fenómeno, el suicidio del agresor y la incidencia del tratamiento mediático [Gender-based femicides: Actual evolution of the phenomenon, the suicide of the aggressor and the incidence of media coverage]. Revista Española de Investigación Criminológica: REIC, 9, 1.

Tranchese, A., & Zollo, S. A. (2013). The Construction of Gender-based Violence in the British Printed and Broadcast Media. Critical Approaches to Discourse Analysis across Disciplines, 7(1), 141–163.

Tsay, R. S. (1989) Identifying Multivariate Time Series Models Journal of Time Series Analysis—Wiley Online Library https://onlinelibrary.wiley.com/doi/10.1111/j.1467–9892.1989.tb00034.x

UN Women (2012) Handbook for National Action Plans on Violence against Women. UN Women – Headquarters. https://www.unwomen.org/en/digital-library/publications/2012/7/handbook-for-national-action-plans-on-violence-against-women

UN Women (2017) Media coverage of gender-based violence—Handbook and Training of Trainers. https://eca.unwomen.org/en/digital-library/publications/2017/09/media-coverage-of-gender-based-violence---handbook-and-training-of-trainers

UN Women—ONU Mujeres (2021). Violence against women prevalence estimates, 2018. Global, regional and national prevalence estimates for intimate partner violence against women and global and regional prevalence estimates for non-partner sexual violence against women https://www.unwomen.org/es/what-we-do/ending-violence-against-women/facts-and-figures

UNESCO (2019) Reporting on violence against women and girls: A handbook for journalists” UNESCO Digital Library. https://unesdoc.unesco.org/ark:/48223/pf0000371524

Veen, H. J. van, Saul, N., Eargle, D., & Mangham, S. W. (2019). Kepler Mapper: A flexible Python implementation of the Mapper algorithm. Journal of Open Source Software, 4(42), 1315. https://doi.org/10.21105/joss.01315

Violenciagenero (2019). Government Delegation against Gender Violence http://www.violenciagenero.igualdad.gob.es/laDelegacionInforma/home.htm

WHO (2013)| Global and regional estimates of violence against women: prevalence and health effects of intimate partner violence and non-partner sexual violence. World Health Organization. https://apps.who.int/iris/handle/10665/85239

Wolf, B. (2018). Gender-based violence in discourse. A comparative study on anti-violence communication initiatives across Europe, in Austria and Spain. https://doi.org/10.5565/rev/

Wong, J. S., & Lee, C. (2018). Extra! Extra! The Importance of Victim-Offender Relationship in Homicide Newsworthiness. Journal of Interpersonal Violence, 886260518789142. https://doi.org/10.1177/0886260518789142

Xue, J., Chen, J., & Gelles, R. (2019). Using Data Mining Techniques to Examine Domestic Violence Topics on Twitter. Violence and Gender, 6(2), 105–114. https://doi.org/10.1089/vio.2017.0066

Downloads

Published

2023-10-17

How to Cite

Bello, H. J., Palomar-Ciria, N., Gallego, E., Jiménez Navascués, L., & Lozano, C. (2023). Big Data Techniques to Study the Impact of Gender-Based Violence in the Spanish News Media. Central European Journal of Communication, 16(1(33), 101-116. https://doi.org/10.51480/1899-5101.16.1(33).6

Issue

Section

Scientific Papers