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To analyze the impact that arXiv is having on the world, in this paper wepropose an arXiv information distribution model on Twitter, which has athree-layer structure: arXiv papers, information spreaders, and informationcollectors. First, we use the HITS algorithm to analyze the arXiv informationdiffusion network with users as nodes, which is created from three types ofbehavior on Twitter regarding arXiv papers: tweeting, retweeting, and liking.Next, we extract communities from the network of information spreaders withpositive authority and hub degrees using the Louvain method, and analyze therelationship and roles of information spreaders in communities using researchfield, linguistic, and temporal characteristics. From our analysis using thetweet and arXiv datasets, we found that information about arXiv paperscirculates on Twitter from information spreaders to information collectors, andthat multiple communities of information spreaders are formed according totheir research fields. It was also found that different communities were formedin the same research field, depending on the research or cultural background ofthe information spreaders. We were able to identify two types of key persons:information spreaders who lead the relevant field in the internationalcommunity and information spreaders who bridge the regional and internationalcommunities using English and their native language. In addition, we found thatit takes some time to gain trust as an information spreader.

Analysis of Leading Communities Contributing to arXiv Information Distribution on Twitter