“The spread of disinformation about science in social media has been a major concern worldwide, especially at a time of crisis in which all institutions that produce knowledge and truth, including science, are delegitimized or discredited by society. given this, the purpose of this research is to map the circulation of information on the most frequent conspiracy theories in brazil, seeking to identify actors, discourses, and interactions on different digital platforms. using a mixed methodology for identifying informational flows among supporters of conspiracy theories on facebook, whatsapp, and youtube, the results show that, even though there is distrust about the relationship between science, government and industry, scientific authority is a symbolic capital of extreme importance for the circulation of information on conspiracy theories related to science.”

“Sentiment analysis has recently become increasingly important with a massive increase in online content. it is associated with the analysis of textual data generated by social media that can be easily accessed, obtained, and analyzed. with the emergence of covid-19, most published studies related to covid-19’s conspiracy theories were surveys on the people’s sentiments and opinions and studied the impact of the pandemic on their lives. just a few studies utilized sentiment analysis of social media using a machine learning approach. these studies focused more on sentiment analysis of twitter tweets in the english language and did not pay more attention to other languages such as arabic. this study proposes a machine learning model to analyze the arabic tweets from twitter. in this model, we apply word2vec for word embedding which formed the main source of features. two pretrained continuous bag-of-words (cbow) models are investigated, and naïve bayes was used as a baseline classifier. several single-based and ensemble-based machine learning classifiers have been used with and without smote (synthetic minority oversampling technique). the experimental results show that applying word embedding with an ensemble and smote achieved good improvement on average of f1 score compared to the baseline classifier and other classifiers (single-based and ensemble-based) without smote.”

“Introduction: google autocomplete algorithms despite recent attention to the impact of social media platforms on political discourse and public opinion, most people locate their news on search engines (robertson et al.). when a user conducts a search, millions of outputs, in the form of videos, images, articles, and websites are sorted to present the most relevant search predictions. google, the most dominant search engine in the world, expanded its search index in 2009 to include the autocomplete function, which provides suggestions for query inputs (dörr and stephan). google’s autocomplete function also allows users to ‘search smarter’ by reducing typing time by 25 percent (baker and potts 189). google’s complex algorithm is impacted upon by factors like search history, location, and keyword searches (karapapa and borghi), and there are policies to ensure the autocomplete function does not contain harmful content. in 2017, google implemented a feedback tool to allow human evaluators to assess the quality of search results; however, the algorithm still provides misleading results that frame far-right actors as neutral. in this article, we use reverse engineering to understand the nature of these algorithms in relation to the descriptive outcome, to illustrate how autocomplete subtitles label conspiracists in three countries. according to google, these ‘subtitles are generated automatically’, further stating that the ‘systems might determine that someone could be called an actor, director, or writer. only one of these can appear as the subtitle’ and that google ‘cannot accept or create custom subtitles’ (google). we focused our attention on well-known conspiracy theorists because of their influence and audience outreach. in this article we argue that these subtitles are problematic because they can mislead the public and amplify extremist views. google’s autocomplete feature is misleading because it does not highlight what is publicly known about these actors. the labels are neutral or positive but never negative, reflecting primary jobs and/or the actor’s preferred descriptions. this is harmful to the public because google’s search rankings can influence a user’s knowledge and information preferences through the search engine manipulation effect (epstein and robertson). users’ preferences and understanding of information can be manipulated based upon their trust in google search results, thus allowing these labels to be widely accepted instead of pr…”

“The antivax movement is now a constant phenomenon with increasing social implications. this study explores how the antivax movement is articulated in romania on the basis of qualitative analysis applied to interviews. our pilot study focuses on the opinions of 100 persons who oppose vaccination interviewed between 2017 and 2020. we conducted both face-to-face and online semistructured interviews to trace the factors determining attitudes against vaccination. to the best of the authors’ knowledge, this is the first such extended study to target individuals rather than groups or media discourse. we strive to provide a multifaceted view on how the antivax phenomenon is taking shape. responses varied in style and length, so we needed to systematize the narratives. we filtered the answers using the interpretive net described by entman (1993), thereby grouping the main narratives into four sections. we then reconstructed the implicit frames used by individuals in interpreting their position. we consider content quality analysis to be a relevant method to reveal the facets and depth of the antivax phenomenon, thereby enabling more complex explanations. we compare the results of this study with rationales stemming from similar investigations conducted around the world and then highlight opinions specific to the romanian public.”

“Cataclysmic changes by the gradual spread of covid-19 have triggered the interest of scientists, scholars, academicians, and linguists in analyzing the discourse related to the spread of the pandemic. the descriptions made by all of these scholars not only contribute to language with linguistic innovations but also cause the emergence of human attitudes and behaviours. at the same time, the issues raised through the language used during the challenging time of such crises shape and reveal several human schemas of language, discourse, society, and culture. several studies on past situations of diseases and calamities have provided critical analyses of these schemas of difficult times in human history. discourses through various linguistic practices in this regard play a crucial role in shaping and demonstrating the schemas of the crisis hit societies. media discourse, specifically, has hidden powers to exercise, identify and report various socio-cultural issues. the current study focuses on finding the themes of socio-cultural attitudes and behaviours that emerged from newspaper editorials published in pakistani newspapers in february, march and april, 2020. to achieve this goal, the corpus-driven analysis of 198 newspaper editorials having 215,842 words was conducted. the study revealed various themes that prevailed in this pre-vaccination period of covid-19 in pakistan. the themes included the metaphoric use of the language such as battle, corps and frontline; racism while naming the virus as china virus or hazara virus; conspiracy theories assumed to be associated with covid-19 spread i.e. suspected involvement of bill gates and the centers for disease control (cdc), us and world health organization (who); negligence on the part of people; and criticism on government for health facilities and implications of globalization. it is concluded, based on these findings, that media representation of pre-vaccination phase of covid-19 in pakistan is loaded with unhealthy discourse which could have been avoided in order to shape positive attitudes and behaviours of the masses.”

“Introduction in this article, we hypothesise how mainstream media coverage can promote the spread of disinformation about covid-19. mainstream media are often discussed as opposed to disinformation (glasser; benkler et al.). while the disinformation phenomenon is related to the intentional production and spread of misleading and false information to influence public opinion (fallis; benkler et al.), mainstream media news is expected to be based on facts and investigation and focussed on values such as authenticity, accountability, and autonomy (hayes et al.). however, journalists might contribute to the spread of disinformation when they skip some stage of information processing and reproduce false or misleading information (himma-kadakas). besides, even when the purpose of the news is to correct disinformation, media coverage might contribute to its dissemination by amplifying it (tsfati et al.). this could be particularly problematic in the context of social media, as users often just read headlines while scrolling through their timelines (newman et al.; ofcom). thus, some users might share news from the mainstream media to legitimate disinformation about covid-19. the pandemic creates a delicate context, as journalists are often pressured to produce more information and, therefore, are more susceptible to errors. in this research, we focussed on the hypothesis that legitimate news can contribute to the spread of disinformation on social media through headlines that reinforce disinformation discourses, even though the actual piece may frame the story differently. the research questions that guide this research are: are urls with headlines that reinforce disinformation discourses and other mainstream media links shared into the same facebook groups? are the headlines that support disinformation discourses shared by facebook users to reinforce disinformation narratives? as a case study, we look at the brazilian disinformation context on covid-19. the discussion about the disease in the country has been highly polarised and politically framed, often with government agents and scientists disputing the truth about facts on the disease (araújo and oliveira; recuero and soares; recuero et al.). particularly, the social media ecosystem seems to play an important role in these disputes, as brazilian president jair bolsonaro and his supporters use it as a key channel to spread disinformation about the virus (lisboa et al.; soares et al.). we use data from publ…”