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Rhythms in Twitter
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posted on 2023-06-07, 23:28 authored by Dan Chalmers, Simon Fleming, Ian WakemanIan Wakeman, Des WatsonWe have examined a Twitter data set, focusing on temporal patterns observed in users' tweets and in the conversations formed by interacting users - rather than a network described by follows relations, or aggregate patterns. We have found the bursty behaviour predicted by Barabasi, but with complex patterns to the bursts. By using a clustering algorithm to group intervals between tweets, we have found that conversations show a different pattern of inter-tweet intervals to individuals, tending to: have a higher volume of quick replies; take shorter breaks; and that the timing is more variable.
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Publication status
- Published
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IEEEPresentation Type
- paper
Event name
proceedings of 1st International Workshop on Social Object Networks (SocialObjects 2011)Event location
Boston, MA, USAEvent type
conferenceDepartment affiliated with
- Informatics Publications
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- No
Peer reviewed?
- Yes
Legacy Posted Date
2012-02-06Usage metrics
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