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Disinformation does not always take the form of a fake news item, it also appears in much less evident formats which are subtly filtered into public opinion, thus making its detection more difficult. A method is proposed in this paper to address the study of "widespread" disinformation by combining social science methods with artificial intelligence and text mining. The case study chosen was the expression "right of self-determination" as a generator of disinformation within the context of the Catalan independence process. The main work hypothesis was that the (intentional or unintentional) confusion around the meaning and scope of this right has become widely extended within the population, generating negative emotions which favour social polarisation. The method utilised had three stages: (1) Description of the disinformation elements surrounding the term with the help of experts; (2) Detection of these elements within a corpus of tweets; (3) Identification of the emotions expressed in the corpus. The results show that the disinformation described by experts clearly dominates the conversation about "self-determination" on Twitter and is associated with a highly negative emotional load in which contempt, hatred, and frustration prevail. [ABSTRACT FROM AUTHOR]

Increased disinformation has been able to flourish in the digital environment. Much of the fake news that circulate social networks is directed against vulnerable groups, such as the LGBTQI+ community. These contents often include hate speech, which has recently experienced a notable increase in Spain. Based on a quantitative and qualitative methodology, the purpose of this research study was, first, to explore the social audience's reaction to four pieces of pseudo-information against LGBTQI+ people posted on Twitter by Mediterráneo Digital between 2018 and 2020, to determine the extent to which this content was considered true or rejected by users of this social network through their comments (N = 596). The four selected publications were considered fake news by recognised verification platforms. Secondly, in addition to the above analysis, six in-depth interviews were carried out with representatives of Spanish LGBTQI+ organisations to explore their perception of this situation and how they addressed disinformation. The results indicated that a high percentage of the responses posted on Twitter consider disinformation against this social group to be true, although a significant proportion of comments also intervened in the conversation to reject these messages. Activists believed pseudo-media (websites that try to imitate conventional news sites but do not respect the diligence and principles of journalism), and social networks are largely responsible for the increase in disinformation, and considered the production of truthful information, educational actions, and collaboration with other groups to be successful strategies in combating disinformation. [ABSTRACT FROM AUTHOR]

In this paper, we sought to model and characterize hate speech against immigrants on Twitter in Spain around the appearance of the far-right party Vox. More than 240,000 tweets that included the term 'Vox' between November 2018 and April 2019 were automatically collected and analyzed. Only 1% of the sample included hate speech expressions. Within this subsample of 1977 messages, we found offenses (56%), incitements to hate (42%), and violent speech (2%). The most frequent terms used were classified into five categories: Spain, Immigration, Government, Islam, and Insults. The most common features were foul language, false or doubtful information, irony, distasteful expressions, humiliation or contempt, physical or psychological threats, and incitement to violence. Using unsupervised topic modeling, we found that the four underlying topics (control of illegal immigration, economic assistance for immigrants, consequences of illegal immigration, and Spain as an arrival point for African immigrants and Islamist terrorism) were similar to those in the discourse of Vox. We conclude that the hate speech against immigrants produced around Vox, and not necessarily by Vox, followed the general patterns of this type of speech detected in previous works, including Islamophobia, offensive language more often than violent language, and the refusal to offer public assistance to these collectives. [ABSTRACT FROM AUTHOR]

In a scenario marked by COVID-19, communication has posed a real challenge for institutions. Since the first case of COVID-19, Spain has faced the enormous challenge of an unprecedented health, economic, and social crisis. The public sphere has put its trust in vaccination as the only chance for the country's recovery. To determine the role played by political leaders in the debate on vaccination and citizens' perception of crisis management, this article analyzes the messages posted on Twitter by the four leaders of the parties with the most representation in parliament: Pedro Sánchez (PSOE), Pablo Casado (PP), Santiago Abascal (Vox), and Yolanda Díaz (Podemos). Using a methodology for comparative content analysis on Twitter, a sample was established that began at the start of the vaccination process and inoculation with the first dose, and covered the entire year that followed. The research results, which contrasted with those collected in demographic surveys, reflected an increase in polarization and electoral use of the vaccine, which took precedence over the awareness-raising discourse typical of public campaigns. [ABSTRACT FROM AUTHOR]