arXiv subjects

Fabiana Zollo

Publications and source records attributed to Fabiana Zollo.

At least 19 recordsLinked to original sources

arXiv2025

Patterns, Models, and Challenges in Online Social Media: A Survey

The rise of digital platforms has enabled the large scale observation of individual and collective behavior through high resolution interaction data. This development has opened new analytical pathways for investigating how information circulates, how opinions evolve, and how coordination emerges in online environments. Yet despite a growing body of research, the field remains fragmented and marked by methodological heterogeneity, limited model validation, and weak integration across domains. This survey offers a systematic synthesis of empirical findings and formal models. We examine platform-level regularities, assess the methodological architectures that generate them, and evaluate the extent to which current modeling frameworks account for observed dynamics. The goal is to consolidate a shared empirical baseline and clarify the structural constraints that shape inference in this domain, laying the groundwork for more robust, comparable, and actionable analyses of online social systems.

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arXiv2025

Towards global equity in political polarization research

With a folk understanding that political polarization refers to socio-political divisions within a society, many have proclaimed that we are more divided than ever. In this account, polarization has been blamed for populism, the erosion of social cohesion, the loss of trust in the institutions of democracy, legislative dysfunction, and the collective failure to address existential risks such as Covid-19 or climate change. However, at a global scale there is surprisingly little academic literature which conclusively supports these claims, with half of all studies being U.S.-focused. Here, we provide an overview of the global state of research on polarization, highlighting insights that are robust across countries, those unique to specific contexts, and key gaps in the literature. We argue that addressing these gaps is urgent, but has been hindered thus far by systemic and cultural barriers, such as regionally stratified restrictions on data access and misaligned research incentives. If continued cross-disciplinary inertia means that these disparities are left unaddressed, we see a substantial risk that countries will adopt policies to tackle polarization based on inappropriate evidence, risking flawed decision-making and the weakening of democratic institutions.

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arXiv2025

Crisis, Country, and Party Lines: Politicians' Misinformation Behavior and Public Engagement

Politicians with large media visibility and social media audiences have a significant influence on public discourse. Consequently, their dissemination of misinformation can have profound implications for society. This study investigated the misinformation-sharing behavior of 3,277 politicians and associated public engagement by using data from X (formerly Twitter) during 2020-2021. The analysis was grounded in a novel and comprehensive dataset including over 400,000 tweets covering multiple levels of governance-national executive, national legislative, and regional executive-in Germany, Italy, the UK, and the USA, representing distinct clusters of misinformation resilience. Striking cross-country differences in misinformation-sharing behavior and public engagement were observed. Politicians in Italy (4.9%) and the USA (2.2%) exhibited the highest rates of misinformation sharing, primarily among far-right and conservative legislators. Public engagement with misinformation also varied significantly. In the USA, misinformation attracted over 2.5 times the engagement of reliable information. In Italy, engagement levels were similar across content types. Italy is unique in crisis-related misinformation, particularly regarding COVID-19, which surpassed general misinformation in both prevalence and audience engagement. These insights underscore the critical roles of political affiliation, governance level, and crisis contexts in shaping the dynamics of misinformation. The study expands the literature by providing a cross-national, multi-level perspective, shedding light on how political actors influence the proliferation of misinformation during crisis.

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arXiv2023

Affective and interactional polarization align across countries

Political polarization plays a pivotal and potentially harmful role in a democracy. However, existing studies are often limited to a single country and one form of polarization, hindering a comprehensive understanding of the phenomena. Here we investigate how affective and interactional polarization are related across nine countries (Canada, France, Germany, Italy, Poland, Spain, Turkey, UK, USA). First, we show that political interaction networks are polarized on Twitter. Second, we reveal that out-group interactions, defined by the network, are more toxic than in-group interactions, meaning that affective and interactional polarization are aligned. Third, we show that out-group interactions receive lower engagement than in-group interactions. Finally, we show that the political right reference lower reliability media than the political left, and that interactions between politically engaged accounts are limited and rarely reciprocated. These results hold across countries and represent a first step towards a more unified understanding of polarization.

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arXiv2023

News and Misinformation Consumption in Europe: A Longitudinal Cross-Country Perspective

The Internet and social media have transformed news availability and accessibility, reshaping information consumption and production. However, they can also facilitate the rapid spread of misinformation, posing significant societal challenges. To combat misinformation effectively, it is crucial to understand the online information environment and news consumption patterns. Most existing research has primarily focused on single topics or individual countries, lacking cross-country comparisons. This study investigated information consumption in four European countries, analyzing three years of Twitter activity from news outlet accounts in France, Germany, Italy, and the UK and focusing on the role of misinformation sources. Our work offers a perspective on how topics of European significance are interpreted across various countries. Results indicate that reliable sources dominate the information landscape, although unreliable content is still present across all countries and topics. While most users engage with reliable sources, a small percentage consume questionable content. Interestingly, few users have a mixed information diet, bridging the gap between questionable and reliable news in the similarity network. Cross-country comparisons revealed differences in audience overlap of news sources, offering valuable guidance for policymakers and scholars in developing effective and tailored solutions to combat misinformation.

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arXiv2023

Social media polarization reflects shifting political alliances in Pakistan

The rise of ideological divides in public discourse has received considerable attention in recent years. However, much of this research has been concentrated on Western democratic nations, leaving other regions largely unexplored. Here, we delve into the political landscape of Pakistan, a nation marked by intricate political dynamics and persistent turbulence. Spanning from 2018 to 2022, our analysis of Twitter data allows us to capture pivotal shifts and developments in Pakistan's political arena. By examining interactions and content generated by politicians affiliated with major political parties, we reveal a consistent and active presence of politicians on Twitter, with opposition parties exhibiting particularly robust engagement. We explore the alignment of party audiences, highlighting a notable convergence among opposition factions over time. Our analysis also uncovers significant shifts in political affiliations, including the transition of politicians to the opposition alliance. Quantitatively, we assess evolving interaction patterns, showcasing the prevalence of homophilic connections while identifying a growing interconnection among audiences of opposition parties. Our study, by accurately reflecting shifts in the political landscape, underscores the reliability of our methodology and social media data as a valuable tool for monitoring political polarization and providing a nuanced understanding of macro-level trends and individual-level transformations.

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arXiv2023

Hurricanes Increase Climate Change Conversations on Twitter

The public understanding of climate change plays a critical role in translating climate science into climate action. In the public discourse, climate impacts are often discussed in the context of extreme weather events. Here, we analyse 65 million Twitter posts and 240 thousand news media articles related to 18 major hurricanes from 2010 to 2022 to clarify how hurricanes impact the public discussion around climate change. First, we analyse news content and show that climate change is the most prominent non-hurricane specific topic discussed by the news media in relation to hurricanes. Second, we perform a comparative analysis between reliable and questionable news media outlets, finding that the language around climate change varies between news media providers. Finally, using geolocated data, we show that accounts in regions affected by hurricanes discuss climate change at a significantly higher rate than accounts in unaffected areas, with references to climate change increasing by, on average, 80% after impact, and up to 200% for the largest hurricanes. Our findings demonstrate how hurricanes have a key impact on the public awareness of climate change.

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arXiv2023

Unveiling the Hidden Agenda: Biases in News Reporting and Consumption

One of the most pressing challenges in the digital media landscape is understanding the impact of biases on the news sources that people rely on for information. Biased news can have significant and far-reaching consequences, influencing our perspectives and shaping the decisions we make, potentially endangering the public and individual well-being. With the advent of the Internet and social media, discussions have moved online, making it easier to disseminate both accurate and inaccurate information. To combat mis- and dis-information, many have begun to evaluate the reliability of news sources, but these assessments often only examine the validity of the news (narrative bias) and neglect other types of biases, such as the deliberate selection of events to favor certain perspectives (selection bias). This paper aims to investigate these biases in various news sources and their correlation with third-party evaluations of reliability, engagement, and online audiences. Using machine learning to classify content, we build a six-year dataset on the Italian vaccine debate and adopt a Bayesian latent space model to identify narrative and selection biases. Our results show that the source classification provided by third-party organizations closely follows the narrative bias dimension, while it is much less accurate in identifying the selection bias. Moreover, we found a nonlinear relationship between biases and engagement, with higher engagement for extreme positions. Lastly, analysis of news consumption on Twitter reveals common audiences among news outlets with similar ideological positions.

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arXiv2022

Growing polarisation around climate change on social media

Climate change and political polarisation are two of the 21st century's critical socio-political issues. Here, we investigate their intersection by studying the discussion around the UN Conference of The Parties on Climate Change (COP) using Twitter data from 2014 to 2021. First, we reveal a large increase in ideological polarisation during COP26, following low polarisation between COP20 and COP25. Second, we show that this increase is driven by growing right-wing activity, a 4-fold increase since COP21 relative to pro-climate groups. Finally, we identify a broad range of ''climate contrarian'' views during COP26, emphasising the theme of ''political hypocrisy'' as a topic of cross-ideological appeal; contrarian views and accusations of hypocrisy have become key themes in the Twitter climate discussion since 2019. With future climate action reliant on negotiations at COP27 and beyond, our results highlight the importance of monitoring polarisation, and its impacts, in the public climate discourse.

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arXiv2021

Lack of evidence for correlation between COVID-19 infodemic and vaccine acceptance

How information consumption affects behaviour is an open and widely debated research question. A popular hypothesis states that the so-called infodemic has a substantial impact on orienting individual decisions. A competing hypothesis stresses that exposure to vast amounts of even contradictory information has little effect on personal choices. The COVID-19 pandemic offered an opportunity to investigate this relationship, analysing the interplay between COVID-19 related information circulation and the propensity of users to get vaccinated. We analyse the vaccine infodemics on Twitter and Facebook by looking at 146M contents produced by 20M accounts between 1 January 2020 and 30 April 2021. We find that vaccine-related news triggered huge interest through social media, affecting attention patterns and the modality in which information was spreading. However, we observe that such a tumultuous information landscape translated only in minimal variations in overall vaccine acceptance as measured by Facebook's daily COVID-19 Trends and Impact Survey (previously known as COVID-19 World Symptoms Survey) on a sample of 1.6M users. Notably, the observation period includes the European Medicines Agency (EMA) investigations over blood clots cases potentially related to vaccinations, a series of events that could have eroded trust in vaccination campaigns. We conclude the paper by investigating the numerical correlation between various infodemics indices and vaccine acceptance, observing strong compatibility with a null model. This finding supports the hypothesis that altered information consumption patterns are not a reliable predictor of collective behavioural change. Instead, wider attention on social media seems to resolve in polarisation, with the vaccine-prone and the vaccine-hesitant maintaining their positions.

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arXiv2021

Online Hate: Behavioural Dynamics and Relationship with Misinformation

Online debates are often characterised by extreme polarisation and heated discussions among users. The presence of hate speech online is becoming increasingly problematic, making necessary the development of appropriate countermeasures. In this work, we perform hate speech detection on a corpus of more than one million comments on YouTube videos through a machine learning model fine-tuned on a large set of hand-annotated data. Our analysis shows that there is no evidence of the presence of "serial haters", intended as active users posting exclusively hateful comments. Moreover, coherently with the echo chamber hypothesis, we find that users skewed towards one of the two categories of video channels (questionable, reliable) are more prone to use inappropriate, violent, or hateful language within their opponents community. Interestingly, users loyal to reliable sources use on average a more toxic language than their counterpart. Finally, we find that the overall toxicity of the discussion increases with its length, measured both in terms of number of comments and time. Our results show that, coherently with Godwin's law, online debates tend to degenerate towards increasingly toxic exchanges of views.

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arXiv2020

Lexical convergence and collective identities on Facebook

Recent studies, targeting Facebook, showed the tendency of users to interact with information adhering to their preferred narrative and to ignore dissenting information. Primarily driven by confirmation bias, users tend to join polarized clusters where they cooperate to reinforce a like-minded system of beliefs, thus facilitating fake news and misinformation cascades. To gain a deeper understanding of these phenomena, in this work we analyze the lexicons used by the communities of users emerging on Facebook around verified and unverified contents. We show how the lexical approach provides important insights about the kind of information processed by the two communities of users and about their overall sentiment. Furthermore, by focusing on comment threads, we observe a strong positive correlation between the lexical convergence of co-commenters and their number of interactions, which in turns suggests that such a trend could be a proxy for the emergence of collective identities and polarization in opinion dynamics.

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arXiv2020

The COVID-19 Social Media Infodemic

We address the diffusion of information about the COVID-19 with a massive data analysis on Twitter, Instagram, YouTube, Reddit and Gab. We analyze engagement and interest in the COVID-19 topic and provide a differential assessment on the evolution of the discourse on a global scale for each platform and their users. We fit information spreading with epidemic models characterizing the basic reproduction numbers $R_0$ for each social media platform. Moreover, we characterize information spreading from questionable sources, finding different volumes of misinformation in each platform. However, information from both reliable and questionable sources do not present different spreading patterns. Finally, we provide platform-dependent numerical estimates of rumors' amplification.

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arXiv2019

(Mis)Information Operations: An Integrated Perspective

The massive diffusion of social media fosters disintermediation and changes the way users are informed, the way they process reality, and the way they engage in public debate. The cognitive layer of users and the related social dynamics define the nature and the dimension of informational threats. Users show the tendency to interact with information adhering to their preferred narrative and to ignore dissenting information. Confirmation bias seems to account for users decisions about consuming and spreading content; and, at the same time, aggregation of favored information within those communities reinforces group polarization. In this work, the authors address the problem of (mis)information operations with a holistic and integrated approach. Cognitive weakness induced by this new information environment are considered. Moreover, (mis)information operations, with particular reference to the Italian context, are considered; and the fact that the phenomenon is more complex than expected is highlighted. The paper concludes by providing an integrated research roadmap accounting for the possible future technological developments.

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arXiv2019

Selective Exposure shapes the Facebook News Diet

The social brain hypothesis fixes to 150 the number of social relationships we are able to maintain. Similar cognitive constraints emerge in several aspects of our daily life, from our mobility up to the way we communicate, and might even affect the way we consume information online. Indeed, despite the unprecedented amount of information we can access online, our attention span still remains limited. Furthermore, recent studies showed the tendency of users to ignore dissenting information but to interact with information adhering to their point of view. In this paper, we quantitatively analyze users' attention economy in news consumption on social media by analyzing 14M users interacting with 583 news outlets (pages) on Facebook over a time span of 6 years. In particular, we explore how users distribute their activity across news pages and topics. We find that, independently of their activity, users show the tendency to follow a very limited number of pages. On the other hand, users tend to interact with almost all the topics presented by their favored pages. Finally, we introduce a taxonomy accounting for users behavior to distinguish between patterns of selective exposure and interest. Our findings suggest that segregation of users in echo chambers might be an emerging effect of users' activity on social media and that selective exposure -- i.e. the tendency of users to consume information interest coherent with their preferences -- could be a major driver in their consumption patterns.

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arXiv2018

Polarization Rank: A Study on European News Consumption on Facebook

The advent of WWW changed the way we can produce and access information. Recent studies showed that users tend to select information that is consistent with their system of beliefs, forming polarized groups of like-minded people around shared narratives where dissenting information is ignored. In this environment, users cooperate to frame and reinforce their shared narrative making any attempt at debunking inefficient. Such a configuration occurs even in the consumption of news online, and considering that 63% of users access news directly form social media, one hypothesis is that more polarization allows for further spreading of misinformation. Along this path, we focus on the polarization of users around news outlets on Facebook in different European countries (Italy, France, Spain and Germany). First, we compare the pages' posting behavior and the users' interacting patterns across countries and observe different posting, liking and commenting rates. Second, we explore the tendency of users to interact with different pages (i.e., selective exposure) and the emergence of polarized communities generated around specific pages. Then, we introduce a new metric -- i.e., polarization rank -- to measure polarization of communities for each country. We find that Italy is the most polarized country, followed by France, Germany and lastly Spain. Finally, we present a variation of the Bounded Confidence Model to simulate the emergence of these communities by considering the users' engagement and trust on the news. Our findings suggest that trust in information broadcaster plays a pivotal role against polarization of users online.

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arXiv2018

Polarization and Fake News: Early Warning of Potential Misinformation Targets

Users polarization and confirmation bias play a key role in misinformation spreading on online social media. Our aim is to use this information to determine in advance potential targets for hoaxes and fake news. In this paper, we introduce a general framework for promptly identifying polarizing content on social media and, thus, "predicting" future fake news topics. We validate the performances of the proposed methodology on a massive Italian Facebook dataset, showing that we are able to identify topics that are susceptible to misinformation with 77% accuracy. Moreover, such information may be embedded as a new feature in an additional classifier able to recognize fake news with 91% accuracy. The novelty of our approach consists in taking into account a series of characteristics related to users behavior on online social media, making a first, important step towards the smoothing of polarization and the mitigation of misinformation phenomena.

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arXiv2018

Polarization of the Vaccination Debate on Facebook

Vaccine hesitancy has been recognized as a major global health threat. Having access to any type of information in social media has been suggested as a potential powerful influence factor to hesitancy. Recent studies in other fields than vaccination show that access to a wide amount of content through the Internet without intermediaries resolved into major segregation of the users in polarized groups. Users select the information adhering to theirs system of beliefs and tend to ignore dissenting information. In this paper we assess whether there is polarization in Social Media use in the field of vaccination. We perform a thorough quantitative analysis on Facebook analyzing 2.6M users interacting with 298.018 posts over a time span of seven years and 5 months. We used community detection algorithms to automatically detect the emergent communities from the users activity and to quantify the cohesiveness over time of the communities. Our findings show that content consumption about vaccines is dominated by the echo-chamber effect and that polarization increased over years. Communities emerge from the users consumption habits, i.e. the majority of users only consumes information in favor or against vaccines, not both. The existence of echo-chambers may explain why social-media campaigns providing accurate information may have limited reach, may be effective only in sub-groups and might even foment further polarization of opinions. The introduction of dissenting information into a sub-group is disregarded and can have a backfire effect, further reinforcing the existing opinions within the sub-group.

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