ELiRF/montero2k

Citation Information

If you use this dataset, please cite the following paper:

@article{iranzo-etal-2024-montero,
    title ={Journalists’ Ethical Responsibility: Tackling Hate Speech Against Women Politicians in Social Media Through Natural Language Processing Techniques},
    author = {Iranzo-Cabrera, Maria and
      Castro-Bleda, Maria Jose and
      Sim{\'o}n-Astudillo, Iris and
      Hurtado, Llu{\'\i}s-F.},
    journal = {Social Science Computer Review},
    year = {2024},
    abstract = { Social media has led to a redefinition of the journalist’s role. Specifically on Twitter, these professionals assume an influential position and their discourse is dominated by personal opinions. Taking into consideration that this platform has proven to be a breeding ground for polarization, digital harassment and hate speech, notably against women politicians, this research aims to analyze journalists’ involvement in this complex scenario. The investigation aims to determine whether, immersed in online and gender defamation campaigns, journalists enhance the quality of public debate or, on the contrary, they reinforce the visibility of this hostile content. To this end, we examined a sample of 63,926 tweets published from 23 to 25 November 2022 related to a campaign of political violence against the Spanish Minister of Equality using Natural Language Processing tools and qualitative content analysis. Results show that during those three days, at least half of the tweets contained hate speech and improper language. In this climate of hostility, journalists participating in the debate not only have an ability to attract likes and retweets but also exhibit polarization and use hate speech. Each ideological position—for and against the Minister—is also reflected in their own uncivil strategies. Under the umbrella of free speech and regardless of argumentative discourses, those journalists who lean towards ideological progressivism tend to insult their opponents, and those on the political right use divisive constructions, stereotyping and irony as attack techniques. }
,
    doi = {10.1177/08944393241269417},
    url = {https://doi.org/10.1177/08944393241269417},
    eprint = {https://doi.org/10.1177/08944393241269417},
    pages = {1--28}
}