Inform or flood: estimating when retweets duplicate

Amit Tiroshi, Tsvi Kuflik, Shlomo Berkovsky

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review


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.
Original languageEnglish
Title of host publicationUser Modeling, Adaptation, and Personalization
Subtitle of host publication21th International Conference, UMAP 2013 Proceedings
EditorsSandra Carberry, Stephan Weibelzahl, Alessandro Micarelli, Giovanni Semeraro
Place of PublicationBerlin
PublisherSpringer, Springer Nature
Number of pages7
ISBN (Electronic)9783642388446
ISBN (Print)9783642388439
Publication statusPublished - 2013
Externally publishedYes

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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