The Impact of COVID-19 on Twitter Ego Networks: Structure, Sentiment, and Topics

Abstract Lockdown measures, implemented by governments during the initial phases of the COVID-19 pandemic to reduce physical contact and limit viral spread, imposed significant restrictions on in-person social interactions. Consequently, individuals turned to online social platforms to maintain connections. Ego networks, which model the organization of personal relationships according to human cognitive constraints on managing meaningful interactions, provide a framework for analyzing such dynamics. The disruption of physical contact and the predominant shift of social life online potentially altered the allocation of cognitive resources dedicated to managing these digital relationships. This research aims to investigate the impact of lockdown measures on the characteristics of online ego networks, presumably resulting from this reallocation of cognitive resources. To this end, a large dataset of Twitter users was examined, covering a seven-year period of activity. Analyzing a seven-year Twitter dataset (including five years pre-pandemic and two years post), we observe clear, though temporary, changes. During lockdown, ego networks expanded, social circles became more structured, and relationships intensified. Simultaneously, we observed an asymmetric emotional response: the proportion of negative interactions showed a significant acceleration, while the proportion of positive interactions remained statistically stable. Thematic diversity, however, did not show a significant increase during the lockdown. Once restrictions were lifted, these structural and emotional shifts largely reverted to pre-pandemic norms, suggesting a temporary adaptation to an extraordinary social context.