What is it about?
In this work it is shown how clustering hashtag trajectories along a Twitter graph can reveal a substantial amount of information about Twitter community structure and how they can be used to recover Twitter functionality and structure. It is shown that functionality can help recover both structure and functionality. The proposed technique has been applied to two large graphs from political Twitter.
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Why is it important?
Community structure discovery in graphs and especially in social media is of paramount importance since it allows effective digital campaigns to be designed and implemented. Moreover, the strong correlation between Twitter functionality and structure is revealed. After all, networks are build to perform some kind of function over their structure.
Perspectives
This work is the first step towards a general analysis of the role of memes, namely rudimentary information elements about culture similar to the biological genes, in graphs. Although hashtags are not the only memes in Twitter, they are the by far the most distinctive.
Georgios Drakopoulos
Ionian University
Read the Original
This page is a summary of: Decomposing Twitter Graphs Based On Hashtag Trajectories: Mining And Clustering Paths Over MongoDB, September 2022, ACM (Association for Computing Machinery),
DOI: 10.1145/3549737.3549768.
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