To maintain popularity on social media over the long term, users need
to shift to a new topic instead of sticking to one topic. When
selecting a new topic, a user needs to consider both its popularity on
the entire social media and its popularity among the current
followers. The former affects the expected number of new followers,
and the latter affects the expected ratio of the current followers the
user can retain after the topic change. The timing is also important.
The user should change to a new topic before the current topic becomes
less popular and the user loses many of the current followers. If the
user change the topic after losing the followers, it is more difficult
to obtain new followers. In this paper, we introduce a new task based
on these observations: recommending appropriate new topics for
currently popular social media users at appropriate timing. As an
example of opportunities in the research on this task, we also propose
a simple method of predicting the popularity a given user would gain
after shifting to a given new topic. Our method predicts it based on
the similarity between the user's current topic and the given new
topic. In our experiment with data collected from X (formerly
Twitter), our method improves the prediction accuracy compared with a
baseline method.
social network, X, Twitter, topic shift, topic selection, popularity, prediction, repost prediction, retweet prediction
Published in Proc. of IEEE BigData, pp.713-718, 2024
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