TY - JOUR
T1 - Comparing the Impact of Social Media Regulations on News Consumption
AU - Etta, Gabriele
AU - Cinelli, Matteo
AU - Galeazzi, Alessandro
AU - Valensise, Carlo Michele
AU - Quattrociocchi, Walter
AU - Conti, Mauro
PY - 2022
Y1 - 2022
N2 - Users online tend to consume information adhering to their system of beliefs and 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 article, 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 toward 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 toward reliable content with a uniform narrative. Gab, instead, offers a more heterogeneous structure where users, independent of their leaning, follow people who are slightly polarized toward questionable news.
AB - Users online tend to consume information adhering to their system of beliefs and 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 article, 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 toward 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 toward reliable content with a uniform narrative. Gab, instead, offers a more heterogeneous structure where users, independent of their leaning, follow people who are slightly polarized toward questionable news.
KW - Blogs
KW - COVID-19
KW - echo chambers
KW - Fake news
KW - fake news
KW - news consumption
KW - Organizations
KW - Pandemics
KW - Regulation
KW - social media.
KW - Social networking (online)
UR - http://www.scopus.com/inward/record.url?scp=85132362088&partnerID=8YFLogxK
U2 - 10.1109/TCSS.2022.3171391
DO - 10.1109/TCSS.2022.3171391
M3 - Article
AN - SCOPUS:85132362088
VL - 10
SP - 1252
EP - 1262
JO - IEEE Transactions on Computational Social Systems
JF - IEEE Transactions on Computational Social Systems
SN - 2329-924X
IS - 3
ER -