A research conducted by the Universitat analyses the role that journalism plays on hate discourses in Twitter.

  • Press Office
  • November 20th, 2024
 
Researcher and professor Maria Iranzo-Cabrera
Researcher and professor Maria Iranzo-Cabrera

A recent research headed by María Iranzo-Cabrera, researcher of the Universitat de València, and published in Social Science Computer Review, analyses journalists implication on the spreading of hate speech against politic women on Twitter. Focusing the case of Irene Montero, minister of Equality in Spain, the research points out worrying information about the professional polarization and the use of this discourse in press contents.

“Toxic platform”, according to The Guardian and “Misinformation network” according to La Vanguardia. These are the two reasons that led this newspapers to leave the social media X, before called Twitter, a week ago. “The academy had already demonstrated that since 2019 it is a breeding ground for polarization, digital bulling and hate speeches, specially suffered by politic women. This tendency has increased since Elon Musk bought Twitter on April 2022. Since then, Twitter amplifies contents with emotional charge, most specially the tweets that express anger”, Maria Iranzo-Cabrera states. Iranzo-Cabrera, together with Maria José Castro-Bleda (Universitat Politècnica de València), Iris Simon-Astudillo (University of Valladolid) y Lluís F.Hurtado (Universitat Politècnica de València), have focused at the role played by journalists who are deep into gender and online defamation campaigns.

The research aimed to determine whether journalists who are immerse in online defamation campaigns improve the quality of public debates, or, on the contrary, reinforce the visibility of these hostile contents. With that purpose on mind, they analysed a sample of 63,926 tweets published between November 23 and 25 of 2022 and related to the campaign of politic violence against the former minister of Equality, Irene Montero, as a result of the declarations made against her by the VOX deputy Carla Toscano. Through the tools of Natural Language Processing and the analysis of the qualitative content, the research highlights that during those three days, “at least the half od the tweets containing the word 'Montero' included hate and inappropriate language”, Castro-Bleda explains.

In this climate of hostility, the 83 journalists that participated in the debate –each one having more of 10,000 followers – not only attracted likes and retweets, but also showed polarization and used hate speech, either their own (37.58%) or through other people's quotes (11.41%).

Each ideological position – in favour or against the minister – is also reflected on their own unpleasant strategies. Under the umbrella of freedom of speech and aside from argumentative discourses, journalists who are leaning more towards ideological progressivism tend to insult their opponents, calling them “fascists”, “Nazi gang” or “set of bastards and crooked bitches”; on the other hand, those leaning towards politic right use dividing phrases, stereotypes and irony as attack techniques. Firstly, they express the meaning of “violence” against Montero, supposedly caused by the approval of the “Only Yes Means Yes” Act. And, secondly, justify the hate campaign by putting the aim at the alleged maltreatment that the ministry and her party have expressed towards the contrary ideological bloc. If we pay attention to the professional positions of those who publish hate speech, we can find redactors (19), columnists (14), pseudo-media directors (7), editors (7), media directors (2), pseudo-media editors (2) and illustrators (4).

Moreover, 42 journalistic enterprises took part in this online debate. A 2.38% of the tweets published by official accounts included hate speech (4), and a 27.38% (48) reproduced other people's hate expressions. These are quotes or video fragments. The 31.25% (15 tweets) include an insult or an offensive term (“violence adoring”, “satrap” and “fascist gang”), and the 29.17% (14 tweets) replicate the stereotype of Montero as a woman who has benefited from a man. Additionally, between the tweets having more of 50 likes and/o retweets (2,239), 138 news were shared, “from which a 76.81 included hate, either in the statements included or directly in the journalist's text”, Simon-Astudillo specifies. 

In the analysed sample it is seen the social unrest with journalism. At least a 10% of the tweets from citizens expressed an explicit critique of the role that media and journalists play, whom they accused of being responsible of sowing hatred or amplifying it with their media coverage. At this point, it must be said that the tweets written by journalists and media were the most spread during the hate campaign, reaching interaction peaks of more than 10,000 likes and 4,000 retweets.

“Journalists have a crucial responsibility as public debate agents, and this analysis shows that in too many cases they have prioritized ideological polarization and their moral superiority conviction over objectivity and respect, ”Iranzo-Cabrera indicates, and she adds: “And when they confine themselves to reproducing others' hate speech, they work as echo chambers for that kind of speech”.

Proposals

For that reason, the researcher team proposes two measures that automatically regulate themselves. On the one hand, when the accounts of the professionals are linked to media on their biography – what happens frequently – , “it is urgent that media provide guidelines to regulate the hate speech expressed by their employees in X”. On the other hands, rules that prevent the excessive spreading of hate speech in journalistic pieces are necessary, not only the ones diffused by third parties but also by journalists themselves. “These requirements are specially necessary in a context of professional discredit as the one we are living in now”, they state.

 

Article:

Iranzo-Cabrera, M., Castro-Bleda, M. J., Simón-Astudillo, I., & Hurtado, L.-F. (2024). Journalists’ Ethical Responsibility: Tackling Hate Speech Against Women Politicians in Social Media Through Natural Language Processing Techniques. Social Science Computer Review, 0(0). https://doi.org/10.1177/08944393241269417