El discurso de odio islamófobo en las redes sociales. Un análisis de las actitudes ante la islamofobia en Twitter

Fuentes-Lara, Cristina; Calderón, Carlos Arcila

doi:10.14198/medcom.23044

Cited by 8 publications

(3 citation statements)

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“…Depending on variables such as level of education, prior knowledge of the topic, age, or social class, respondents are predisposed to show opinions contrary to their thinking if their position is not socially accepted or politically correct (Gallacher et al 2021). The social desirability bias is more evident regarding issues such as gender, racism, or the environment because there is greater social polarization (Larson 2019;Fuentes-Lara and Arcila-Calderón 2023), but we also observe it for health issues, e.g., for photoprotection, where society rejects being judged for not protecting themselves from the sun (Galán et al 2011).…”

Section: Methodsmentioning

confidence: 70%

Photoprotection and Skin Cancer on X/Twitter: Analysis of Misinformation, Communication Challenges, and Attitudes in the Spanish Community

Fuentes-Lara,

Poch Butler,

Humanes

et al. 2024

Journalism and Media

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This paper delves into the challenges faced by scientists to effectively communicate regarding photoprotection and skin cancer as a result of the pervasive, harmful effects of disinforming messages. In order to do so, the Spanish population’s understanding of photoprotection and skin cancer is examined. This paper is as an extension of the COMUNICANCER initiative, the ultimate goal of which is to establish protocols for producing and disseminating accurate content that raises the awareness of skin cancer-related dangers, as well as transferring knowledge on health prevention. Therefore, we have monitored the prevalence of misinformation and lack of information regarding sun photoprotection in Spain, aiming to reflect, ultimately, on the added difficulties faced by the scholarly community to disseminate accurate content in today’s communication environment, which has become even more complex due to the distorting influence of disinformation. Employing a quantitative methodology, the research involved a comprehensive analysis of 2498 Spanish-language tweets related to skin cancer and photoprotection collected between August 2021 and August 2022. The study proves that scientists face a social media landscape, particularly on X/Twitter, where there is not only a lack of comprehensive information on the various dimensions of skin cancer, its prevention, and treatment, but which also serves as a breeding ground for the dissemination of inaccurate and misleading information regarding sun-related health risks and preventive measures. This leads to an urgent need to develop strategies aimed at fostering comprehensive and accurate information dissemination, especially regarding health information, due to the critical effect this can have on people and public health systems.

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Section: Methodsmentioning

confidence: 70%

Photoprotection and Skin Cancer on X/Twitter: Analysis of Misinformation, Communication Challenges, and Attitudes in the Spanish Community

Fuentes-Lara,

Poch Butler,

Humanes

et al. 2024

Journalism and Media

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“…164 [213] The impact of social media on panic during the COVID-19 pandemic in iraqi kurdistan: Online questionnaire study 165 [214] COVID-19 and the 5G conspiracy theory: Social network analysis of twitter data 166 [215] From disinformation to fact-checking: How Ibero-American fact-checkers on Twitter combat fake news 167 [216] Tracking social media discourse about the COVID-19 pandemic: Development of a public coronavirus Twitter data set 168 [217] Mining physicians' opinions on social media to obtain insights into COVID-19: Mixed methods analysis 169 [218] A new application of social impact in social media for overcoming fake news in health 170 [219] Islamophobic hate speech on social networks. An analysis of attitudes to Islamophobia on Twitter [El discurso de odio islamo ´fobo en las redes sociales.…”

Section: Id Document Referencementioning

confidence: 99%

Mapping automatic social media information disorder. The role of bots and AI in spreading misleading information in society

Tomassi,

Falegnami,

Romano

2024

PLoS ONE

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This paper presents an analysis on information disorder in social media platforms. The study employed methods such as Natural Language Processing, Topic Modeling, and Knowledge Graph building to gain new insights into the phenomenon of fake news and its impact on critical thinking and knowledge management. The analysis focused on four research questions: 1) the distribution of misinformation, disinformation, and malinformation across different platforms; 2) recurring themes in fake news and their visibility; 3) the role of artificial intelligence as an authoritative and/or spreader agent; and 4) strategies for combating information disorder. The role of AI was highlighted, both as a tool for fact-checking and building truthiness identification bots, and as a potential amplifier of false narratives. Strategies proposed for combating information disorder include improving digital literacy skills and promoting critical thinking among social media users.

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“…In this context, there are numerous studies that provided an approach to the problem in Spain, such as the one developed by Fuentes-Lara and Arcila-Calderón (2023), where Islamophobic hate manifestations were studied on Twitter from hashtags directly related to hatred toward this community, or the study carried out by Zamora-Medina et al (2021), where the impact of a campaign against Islamophobia on Twitter was quantitatively analyzed. Another example is the work carried out by the Ministry of Inclusion, Social Security, and Migration through the Spanish Observatory of Racism and Xenophobia (OBERAXE), in which indicators were established to measure hate speech online.…”

Section: Introductionmentioning

confidence: 99%

The Conversation around Islam on Twitter: Topic Modeling and Sentiment Analysis of Tweets about the Muslim Community in Spain since 2015

González-Baquero,

Amores,

Arcila-Calderón

2023

Religions

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Social media, especially Twitter, has become a platform where hate, toxic, intolerant, and discriminatory speech is increasingly spread. These messages are aimed at different vulnerable social groups, due to some of their differentiating characteristics with respect to the dominant one, whether they are phenotypic, religious, cultural, gender, sexual, etc. Of all these minorities, one of the most affected is the Muslim community, especially since the beginning of the Mediterranean refugee crisis, during which migration from the Middle East and North Africa increased considerably. Spain does not escape this reality as, given its proximity to Morocco, it is one of the main destinations for migrants from North Africa. In this context, there are already several studies focused on specifically investigating Islamophobic speech disseminated on social platforms, normally focused on specific cases. However, there are still no studies focused on analyzing the entire conversation around Islam and the Muslim community that takes place on Twitter and in a southern European country such as Spain, aiming to identify the latent sentiments and the main underlying topics and their characteristics, which would help to relativize and dimension the relevance of Islamophobic messages, as well as to analyze them from a more solid base. The main objective of the present study is to identify the most frequent words, the main underlying topics, and the latent sentiments that predominate in the general conversation about Islam and the Muslim community on Twitter in Spain and in Spanish during the last 8 years. To do this, 190,320 messages that included keywords related to Muslim culture and religion were collected and analyzed using computational techniques. The findings show that the most frequent words in these messages were mostly descriptive and not derogatory, and the predominant latent topics were mostly neutral and informative, although two of them could be considered reliable indicators of Islamophobic rejection. Similarly, while the overall average sentiment in this conversation trended negatively, neutral and positive messages were more prevalent. However, in the negative messages, the sentiment was considerably more pronounced.

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El discurso de odio islamófobo en las redes sociales. Un análisis de las actitudes ante la islamofobia en Twitter

Cited by 8 publications

References 20 publications

Photoprotection and Skin Cancer on X/Twitter: Analysis of Misinformation, Communication Challenges, and Attitudes in the Spanish Community

Photoprotection and Skin Cancer on X/Twitter: Analysis of Misinformation, Communication Challenges, and Attitudes in the Spanish Community

Mapping automatic social media information disorder. The role of bots and AI in spreading misleading information in society

The Conversation around Islam on Twitter: Topic Modeling and Sentiment Analysis of Tweets about the Muslim Community in Spain since 2015

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