Abstract
The social graphs of Twitter users often overlap, such that retweets may cause duplicate posts is a user’s incoming stream of tweets. Hence, it is important for the retweets to strike the balance between sharing information and flooding the recipients with redundant tweets. In this work, we present an exploratory analysis that assesses the degree of duplication caused by a set of real retweets. The results of the analysis show that although the overall duplication is not severe, high degree of duplication is caused by tweets of users with a small number of followers, which are retweeted by users with a small number of followers. We discuss the limitations of this work and propose several enhancements that we intend to pursue in the future.
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Tiroshi, A., Kuflik, T., Berkovsky, S. (2013). Inform or Flood: Estimating When Retweets Duplicate. In: Carberry, S., Weibelzahl, S., Micarelli, A., Semeraro, G. (eds) User Modeling, Adaptation, and Personalization. UMAP 2013. Lecture Notes in Computer Science, vol 7899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38844-6_22
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DOI: https://doi.org/10.1007/978-3-642-38844-6_22
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