Journal article
Between news and history: identifying networked topics of collective attention on Wikipedia
- Abstract:
- The digital information landscape has introduced a new dimension to understanding how we collectively react to new information and preserve it at the societal level. This, together with the emergence of platforms such as Wikipedia, has challenged traditional views on the relationship between current events and historical accounts of events, with an ever-shrinking divide between “news” and “history”. Wikipedia’s place as the Internet’s primary reference work thus poses the question of how it represents both traditional encyclopaedic knowledge and evolving important news stories. In other words, how is information on and attention towards current events integrated into the existing topical structures of Wikipedia? To address this, we develop a temporal community detection approach towards topic detection that takes into account both short term dynamics of attention as well as long term article network structures. We apply this method to a dataset of one year of current events on Wikipedia to identify clusters of Wikipedia articles related to news events, distinct from those that would be found solely from page view time series correlations or static network structure. We are able to resolve the topics that more strongly reflect unfolding current events vs more established knowledge by the relative importance of collective attention dynamics vs link structures. We also offer important developments by identifying and describing the emergent topics on Wikipedia. This work provides a means of distinguishing how these information and attention clusters are related to Wikipedia’s twin faces of encyclopaedic knowledge and current events—crucial to understanding the production and consumption of knowledge in the digital age.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 10.3MB, Terms of use)
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- Publisher copy:
- 10.1007/s42001-023-00215-w
Authors
+ Engineering and Physical Sciences Research Council
More from this funder
- Grant:
- EP/V013068/1
- EP/V03474X/1
- Publisher:
- Springer
- Journal:
- Journal of Computational Social Science More from this journal
- Volume:
- 6
- Issue:
- 2
- Pages:
- 845-875
- Publication date:
- 2023-07-08
- Acceptance date:
- 2023-06-06
- DOI:
- EISSN:
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2432-2725
- ISSN:
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2432-2717
- Language:
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English
- Keywords:
- Pubs id:
-
1353876
- Local pid:
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pubs:1353876
- Deposit date:
-
2023-06-06
Terms of use
- Copyright holder:
- Gildersleve et al.
- Copyright date:
- 2023
- Rights statement:
- © The Author(s) 2023. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
- Licence:
- CC Attribution (CC BY)
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