Online Engagement with Retracted Articles: Who, When, and How?
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2022
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| _version_ | 1866910310241140736 |
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| author | Dambanemuya, Henry K. Abhari, Rod Vincent, Nicholas Horvát, Emőke-Ágnes |
| author_facet | Dambanemuya, Henry K. Abhari, Rod Vincent, Nicholas Horvát, Emőke-Ágnes |
| contents | Retracted research discussed on social media can spread misinformation. Yet we lack an understanding of how retracted articles are mentioned by academic and non-academic users. This is especially relevant on Twitter due to the platform's prominent role in science communication. Here, we analyze the pre- and post-retraction differences in Twitter attention and engagement metrics for over 3,800 retracted English-language articles alongside comparable non-retracted articles. We subset these findings according to five user types detected by our supervised learning classifier: members of the public, academics, bots, science practitioners, and science communicators. We find that retracted articles receive greater user attention (tweet count) and engagement (likes, retweets, and replies) than non-retracted articles, especially among members of the public and bots, with the majority of user engagement happening before retraction. Our results highlight the prominent role of non-experts in discussions of retracted research and suggest an opportunity for social media platforms to contribute towards early detection of problematic scientific research online. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2203_04228 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Online Engagement with Retracted Articles: Who, When, and How? Dambanemuya, Henry K. Abhari, Rod Vincent, Nicholas Horvát, Emőke-Ágnes Social and Information Networks K.4.0 Retracted research discussed on social media can spread misinformation. Yet we lack an understanding of how retracted articles are mentioned by academic and non-academic users. This is especially relevant on Twitter due to the platform's prominent role in science communication. Here, we analyze the pre- and post-retraction differences in Twitter attention and engagement metrics for over 3,800 retracted English-language articles alongside comparable non-retracted articles. We subset these findings according to five user types detected by our supervised learning classifier: members of the public, academics, bots, science practitioners, and science communicators. We find that retracted articles receive greater user attention (tweet count) and engagement (likes, retweets, and replies) than non-retracted articles, especially among members of the public and bots, with the majority of user engagement happening before retraction. Our results highlight the prominent role of non-experts in discussions of retracted research and suggest an opportunity for social media platforms to contribute towards early detection of problematic scientific research online. |
| title | Online Engagement with Retracted Articles: Who, When, and How? |
| topic | Social and Information Networks K.4.0 |
| url | https://arxiv.org/abs/2203.04228 |