Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters

Conversations on Twitter create networks with identifiable contours as people reply to and mention one another in their tweets. These conversational structures differ, depending on the subject and the people driving the conversation. Six structures are regularly observed: divided, unified, fragmented, clustered, and inward and outward hub and spoke structures. These are created as individuals choose whom to reply to or mention in their Twitter messages and the structures tell a story about the nature of the conversatio

Political polarization of news media and influencers on Twitter in the 2016 and 2020 US presidential elections

Social media has been transforming political communication dynamics for over a decade. Here using nearly a billion tweets, we analyse the change in Twitter’s news media landscape between the 2016 and 2020 US presidential elections. Using political bias and fact-checking tools, we measure the volume of politically biased content and the number of users propagating such information. We then identify influencers—users with the greatest ability to spread news in the Twitter network. We observe that the fraction of fake and extremely biased content declined between 2016 and 2020. However, results show increasing echo chamber behaviours and latent ideological polarization across the two elections at the user and influencer levels

The far-right’s influence on Twitter during the 2018 Andalusian elections: an approach through political leaders

New technologies allow politicians to spread their messages omitting the role of mediators. In this context, the Internet has also promoted the emergence of a new actor, digital opinion leaders, who go beyond traditional politics and seek to set the public agenda. One of the main questions nowadays is whether social media, and in particular Twitter as a consolidated tool for political communication, is only used as a sounding board for their political statements, spurring the messages of populist forces. With this in mind, the main objective of this research is to explore the influence of the far-right in the public debate of political leaders on Twitter, analyzing the specific case of the Andalusian regional elections held in December 2018. These elections can be considered a political turning point, with an extreme right party winning seats in a Spanish regional election for the first time in 35 years. In this paper we analyze if Vox used a differentiated strategy via this social network compared to the candidates of the traditional parties: PSOE, PP, Ciudadanos, and Adelante Andalucía. Using content analysis on Twitter as a method, this research determines how Vox candidates worked as influencers of the digital political debate, despite being extra-parliamentary. Vox marked the agenda for the rest of the leaders, while generating great expectation among the audience

Bots increase exposure to negative and inflammatory content in online social systems

Societies are complex systems which tend to polarize into sub-groups of individuals with dramatically opposite perspectives. This phenomenon is reflected -- and often amplified -- in online social networks where, however, humans are no more the only players, and co-exist alongside with social bots, i.e., software-controlled accounts. Analyzing large-scale social data collected during the Catalan referendum for independence on October 1, 2017, consisting of nearly 4 millions Twitter posts generated by almost 1 million users, we identify the two polarized groups of Independentists and Constitutionalists and quantify the structural and emotional roles played by social bots. We show that bots act from peripheral areas of the social system to target influential humans of both groups, bombarding Independentists with violent contents, increasing their exposure to negative and inflammatory narratives and exacerbating social conflict online. Our findings stress the importance of developing countermeasures to unmask these forms of automated social manipulation.Comment: 8 pages, 5 figure

#HashtagSolidarities: Twitter debates and networks in the MENA region

During the course of the so-called Arab Spring, observers were quick to refer to the uprisings as »Facebook revolutions« or »Twitter revolutions«. Although the important role of social media in the 2011 upheavals in the Middle East and North Africa (MENA) is widely acknowledged, its impact on political processes in the region remains contested and contradictory. Rather than looking at social media through a transformation or security lens, the research presented here focused on how debates on three events in the MENA region – the emergence of a video of a rape on Cairo’s Tahrir Square in June 2014, anti-fracking protests in southern Algeria in early 2015, and Saudi Arabia’s military intervention in Yemen in March 2015 – unfolded on Twitter. Closely tracing Twitter debates on these incidents shed light on Twitter’s role in important social and political discussions as well as on the scope and patterns of Twitter networks and digital solidarities. In other words, it highlighted the various ways in which Twitter was used by ordinary people, activists, media outlets, and officials, and in doing so, it provides an idea of the political impact such debates can have via Twitter. The research also revealed that the breadth of opinion on Twitter far exceeds that of traditional media in the MENA region, and the more repressive a context, the more important Twitter becomes. Furthermore, Twitter, in forging digital solidarities, contributes to deepening existing social and political cleavages. That is, the platform is not an autonomous digital space following logics different from those in the physical world. Rather, the dynamics of Twitter are strongly driven by local historical experience, social patterns, and national politics. (Autorenreferat

Modeling and Analyzing Collective Behavior Captured by Many-to-Many Networks

L'abstract è presente nell'allegato / the abstract is in the attachmen

Journalist-twitterers as political influencers in Brazil : narratives and disputes towards a new intermediary model

The ascendency of Jair Bolsonaro to the presidency of Brazil in 2018 put the role of traditional media companies and journalists under the spotlight. Bad news or opinions against his government have been officially treated as fake, inaccurate, or false information. In this context, data show a decrease in news trust and growing news consumption through platforms. According to the 2021 Reuters Institute report on news trust, only 21% of Brazilians trust the press as an institution, with 71% using social media platforms to be informed. As part of a broad and complex crisis of the traditional intermediary model, several journalists appeared in the Brazilian public sphere as influencers on social media platforms such as Twitter. Based on a qualitative perspective, this article aims to research the role of journalists as political influencers and their use of Twitter to express their voices. A sample of 10 journalists with more than 10,000 followers on Twitter, five working for traditional media and five from native digital media, were interviewed in depth. We realized that they use their digital capital in two political directions. On the one hand, as part of a digital strategy promoted by media outlets to gain attention and call the audience, journalists share their spots and comments on daily issues. On the other hand, in a polarized political context, journalists have found Twitter a means to express their voices in a context of increasing violence and restrictions on free expression among this collective

Astroturfing as a strategy for manipulating public opinion on Twitter during the pandemic in Spain

This work aims to establish whether astroturfing was used during the Covid-19 pandemic to manipulate Spanish public opinion through Twitter. This study analyzes tweets published in Spanish and geolocated in the Philippines, and its first objective is to determine the existence of an organized network that directs its messages mainly towards Spain. To determine the non-existence of a random network, a preliminary collection of 1,496,596 tweets was carried out. After determining its 14 main clusters, 280 users with a medium-low profile of participation and micro- and nano-influencer traits were randomly selected and followed for 103 days, for a total of 309,947 tweets. Network science, text mining, sentiment and emotion, and bot probability analyses were performed using Gephi and R. Their network structure suggests an ultra-small-world phenomenon, which would determine the existence of a possible organized network that tries not to be easily identifiable. The data analyzed confirm a digital communication scenario in which astroturfing is used as a strategy aimed at manipulating public opinion through non-influencers (cybertroops). These users create and disseminate content with proximity and closeness to different groups of public opinion, mixing topics of general interest with disinformation or polarized content

Astroturfing as a strategy for manipulating public opinion on Twitter during the pandemic in Spain

This work aims to establish whether astroturfing was used during the Covid-19 pandemic to manipulate Spanish public opinion through Twitter. This study analyzes tweets published in Spanish and geolocated in the Philippines, and its first objective is to determine the existence of an organized network that directs its messages mainly towards Spain. To determine the non-existence of a random network, a preliminary collection of 1,496,596 tweets was carried out. After determining its 14 main clusters, 280 users with a medium-low profile of participation and micro- and nano-influencer traits were randomly selected and followed for 103 days, for a total of 309,947 tweets. Network science, text mining, sentiment and emotion, and bot probability analyses were performed using Gephi and R. Their network structure suggests an ultra-small-world phenomenon, which would determine the existence of a possible organized network that tries not to be easily identifiable. The data analyzed confirm a digital communication scenario in which astroturfing is used as a strategy aimed at manipulating public opinion through non-influencers (cybertroops). These users create and disseminate content with proximity and closeness to different groups of public opinion, mixing topics of general interest with disinformation or polarized content