Community evolution in retweet networks

Abstract

Communities in social networks often reflect close social ties between their members and their evolution through time. We propose an approach that tracks two aspects of community evolution in retweet networks: flow of the members in, out and between the communities, and their influence. We start with high resolution time windows, and then select several timepoints which exhibit large differences between the communities. For community detection, we propose a two-stage approach. In the first stage, we apply an enhanced Louvain algorithm, called Ensemble Louvain, to find stable communities. In the second stage, we form influence links between these communities, and identify linked super-communities. For the detected communities, we compute internal and external influence, and for individual users, the retweet h-index influence. We apply the proposed approach to three years of Twitter data of all Slovenian tweets. The analysis shows that the Slovenian tweetosphere is dominated by politics, that the left-leaning communities are larger, but that the right-leaning communities and users exhibit significantly higher impact. An interesting observation is that retweet networks change relatively gradually, despite such events as the emergence of the Covid-19 pandemic or the change of government.

References in corpus (17)

• Fast unfolding of communities in large networks
• Modularity and community structure in networks
• An index to quantify an individual's scientific research output
• Comparing community structure identification
• Temporal Networks
• Community detection algorithms: a comparative analysis
• Community detection in networks: A user guide
• The performance of modularity maximization in practical contexts
• Consensus clustering in complex networks
• Community Discovery in Dynamic Networks: a Survey
• A Classification for Community Discovery Methods in Complex Networks
• Detecting the community structure and activity patterns of temporal networks: a non-negative tensor factorization approach
• Sustained Online Amplification of COVID-19 Elites in the United States
• Cohesion and Coalition Formation in the European Parliament: Roll-Call Votes and Twitter Activities
• Retweet communities reveal the main sources of hate speech
• Ensemble approaches for improving community detection methods
• Community detection for interaction networks

Cited by in corpus (4)

• Retweet communities reveal the main sources of hate speech
• Bow-Tie Structures of Twitter Discursive Communities
• Enhancing deep neural networks with morphological information
• Mixbiotic society measures: Assessment of community well-going as living system