Domain-based user embedding for competing events on social media
- URL: http://arxiv.org/abs/2308.14806v2
- Date: Wed, 30 Aug 2023 07:07:05 GMT
- Title: Domain-based user embedding for competing events on social media
- Authors: Wentao Xu, Kazutoshi Sasahara
- Abstract summary: We propose a user embedding method based on the URL domain co-occurrence network, which is simple but effective for representing social media users in competing events.
Our results revealed that user embeddings generated directly from the retweet network, and those based on language, performed below expectations.
These findings suggest that the domain-based user embedding can serve as an effective tool to characterize social media users participating in competing events.
- Score: 4.1245904895794085
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Online social networks offer vast opportunities for computational social
science, but effective user embedding is crucial for downstream tasks.
Traditionally, researchers have used pre-defined network-based user features,
such as degree, and centrality measures, and/or content-based features, such as
posts and reposts. However, these measures may not capture the complex
characteristics of social media users. In this study, we propose a user
embedding method based on the URL domain co-occurrence network, which is simple
but effective for representing social media users in competing events. We
assessed the performance of this method in binary classification tasks using
benchmark datasets that included Twitter users related to COVID-19 infodemic
topics (QAnon, Biden, Ivermectin). Our results revealed that user embeddings
generated directly from the retweet network, and those based on language,
performed below expectations. In contrast, our domain-based embeddings
outperformed these methods while reducing computation time. These findings
suggest that the domain-based user embedding can serve as an effective tool to
characterize social media users participating in competing events, such as
political campaigns and public health crises.
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