Direct and Indirect Influence on Likes in Social Media
2026-06-22 • Social and Information Networks
Social and Information NetworksComputers and Society
AI summaryⓘ
The authors studied how people liking posts on the VKontakte social network are influenced by others. They found that a user is more likely to like a post if people close to them, especially those one or two steps away in the network, are active. This influence is strong even if the user’s direct friends are not active, suggesting indirect social effects. They also showed that having active friends from different groups increases the chance of liking.
social contagiononline social networksVKontaktelocal networknetwork distanceindirect influencestructural diversityconnected componentsliking behaviorsocial influence
Authors
Ivan Kozitsin, Anton V. Proskurnikov
Abstract
The present study investigates direct and indirect social contagion mechanisms in an online social network environment. Using a large-scale dataset comprising approximately 290,000 users from the VKontakte platform, we examine the factors associated with the probability that a user likes a post. Our analysis shows that, while demographic and structural characteristics of individual nodes, such as gender and degree, contribute to the observed dynamics, the strongest associations arise from activity in the user's local network. In particular, active nodes (users who have already liked the post) at distances d = 1 and d = 2 play a central role in shaping liking behavior. We find a substantial association between second-order activity and liking probability, which persists even in the absence of active direct neighbors and is consistent with indirect influence pathways in the network. No significant association is detected for nodes at distance three or beyond. The results also support the structural diversity hypothesis: the number of connected components among active friends is a significant predictor of liking.