Investigate human behavior during ramadan through network structure: Evidence from Twitter

This paper studies online behavior during the holy month of Ramadan as reflected in tweeting patterns on the popular social media platform Twitter. In the first study of its kind using Twitter data from the United Arab Emirates (UAE), interaction networks before, during and after Ramadan are extracted and analyzed. We examine the network structure via the field decomposition of Weakly Connected Components (WCC), degree distribution, degree mixing, clustering distribution, clustering mixing and diameter statistics. A number of interesting structural features were detected which were subjected to further analysis. Some of these are common to the entire dataset while others were unique to specific periods (either during Ramadan, or in the two adjacent months). While preliminary in nature, these results were extremely promising and strongly motivate subsequent research efforts on this topic.