arXiv subjects

Gabriele Etta

Publications and source records attributed to Gabriele Etta.

7 recordsLinked to original sources

arXiv2024

Evaluating the effect of viral news on social media engagement

This study examines Facebook and YouTube content from over a thousand news outlets in four European languages from 2018 to 2023, using a Bayesian structural time-series model to evaluate the impact of viral posts. Our results show that most viral events do not significantly increase engagement and rarely lead to sustained growth. The virality effect usually depends on the engagement trend preceding the viral post, typically reversing it. When news emerges unexpectedly, viral events enhances users' engagement, reactivating the collective response process. In contrast, when virality manifests after a sustained growth phase, it represents the final burst of that growth process, followed by a decline in attention. Moreover, quick viral effects fade faster, while slower processes lead to more persistent growth. These findings highlight the transient effect of viral events and underscore the importance of consistent, steady attention-building strategies to establish a solid connection with the user base rather than relying on sudden visibility spikes.

cs.SI↗

arXiv2023

The Drivers of Global News Spreading Patterns

The web radically changed the dissemination of information and the global spread of news. In this study, we aim to reconstruct the connectivity patterns within nations shaping news propagation globally in 2022. We do this by analyzing a dataset of unprecedented size, containing 140 million news articles from 183 countries and related to 37,802 domains in the GDELT database. Unlike previous research, we focus on the sequential mention of events across various countries, thus incorporating a temporal dimension into the analysis of news dissemination networks. Our results show a significant imbalance in online news spreading. We identify news superspreaders forming a tightly interconnected rich club, exerting significant influence on the global news agenda. To further investigate the mechanisms underlying news dissemination and the shaping of global public opinion, we model countries' interactions using a gravity model, incorporating economic, geographical, and cultural factors. Consistent with previous studies, we find that countries' GDP is one of the main drivers to shape the worldwide news agenda.

cs.SI↗

arXiv2022

Characterizing Engagement Dynamics across Topics on Facebook

Social media platforms heavily changed how users consume and digest information and, thus, how the popularity of topics evolves. In this paper, we explore the interplay between the virality of controversial topics and how they may trigger heated discussions and eventually increase users' polarization. We perform a quantitative analysis on Facebook by collecting $\sim57M$ posts from $\sim2M$ pages and groups between 2018 and 2022, focusing on engaging topics involving scandals, tragedies, and social and political issues. Using logistic functions, we quantitatively assess the evolution of these topics finding similar patterns in their engagement dynamics. Finally, we show that initial burstiness may predict the rise of users' future adverse reactions regardless of the discussed topic.

cs.SI↗

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.

physics.soc-ph↗

arXiv2021

Information Consumption and Social Response in a Segregated Environment: the Case of Gab

Most of the information operations involve users who may foster polarization and distrust toward science and mainstream journalism, without these users being conscious of their role. Gab is well known to be an extremist-friendly platform that performs little control on the posted content. Thus it represents an ideal benchmark for studying phenomena potentially related to polarization such as misinformation spreading. The combination of these factors may lead to hate as well as to episodes of harm in the real world. In this work we provide a characterization of the interaction patterns within Gab around the COVID-19 topic. To assess the spreading of different content type, we analyze consumption patterns based on both interaction type and source reliability. Overall we find that there are no strong statistical differences in the social response to questionable and reliable content, both following a power law distribution. However, questionable and reliable sources display structural and topical differences in the use of hashtags. The commenting behaviour of users in terms of both lifetime and sentiment reveals that questionable and reliable posts are perceived in the same manner. We can conclude that despite evident differences between questionable and reliable posts Gab users do not perform such a differentiation thus treating them as a whole. Our results provide insights toward the understanding of coordinated inauthentic behavior and on the early-warning of information operation.

cs.SI↗

arXiv2021

News consumption and social media regulations policy

Users online tend to consume information adhering to their system of beliefs and to ignore dissenting information. During the COVID-19 pandemic, users get exposed to a massive amount of information about a new topic having a high level of uncertainty. In this paper, we analyze two social media that enforced opposite moderation methods, Twitter and Gab, to assess the interplay between news consumption and content regulation concerning COVID-19. We compare the two platforms on about three million pieces of content analyzing user interaction with respect to news articles. We first describe users' consumption patterns on the two platforms focusing on the political leaning of news outlets. Finally, we characterize the echo chamber effect by modeling the dynamics of users' interaction networks. Our results show that the presence of moderation pursued by Twitter produces a significant reduction of questionable content, with a consequent affiliation towards reliable sources in terms of engagement and comments. Conversely, the lack of clear regulation on Gab results in the tendency of the user to engage with both types of content, showing a slight preference for the questionable ones which may account for a dissing/endorsement behavior. Twitter users show segregation towards reliable content with a uniform narrative. Gab, instead, offers a more heterogeneous structure where users, independently of their leaning, follow people who are slightly polarized towards questionable news.

cs.SI↗

arXiv2021

Entropy and complexity unveil the landscape of memes evolution

On the Internet, information circulates fast and widely, and the form of content adapts to comply with users' cognitive abilities. Memes are an emerging aspect of the internet system of signification, and their visual schemes evolve by adapting to a heterogeneous context. A fundamental question is whether they present culturally and temporally transcendent characteristics in their organizing principles. In this work, we study the evolution of 2 million visual memes from Reddit over ten years, from 2011 to 2020, in terms of their statistical complexity and entropy. We find support for the hypothesis that memes are part of an emerging form of internet metalanguage: on one side, we observe an exponential growth with a doubling time of approximately 6 months; on the other side, the complexity of memes contents increases, allowing and adapting to represent social trends and attitudes.

physics.soc-ph↗