Abstract
Addressing the climate crisis calls for global efforts to mitigate greenhouse gas emissions, with effective mitigation efforts depending on an informed public with a high degree of climate change awareness. This study examines global engagement with climate change and related concepts through an analysis of around 517 Million Wikipedia pageviews of 3965 items from WikiProject Climate Change across 213 countries in the years 2017 to 2022. We take advantage of Wikimedia Foundation's differentially-private daily pageview dataset, which makes it possible to study Wikipedia viewing behavior in a language edition agnostic way and on a per-country basis. Temporal analysis reveals a stagnant engagement with climate change articles, contrary to societal trends, possibly due to the attitude-behavior gap. We also found substantial regional differences, with countries from the global north displaying greater traffic compared to the global south. Specific events, notably Greta Thunberg's speech at the UN climate summit in 2019, drive peaks in climate change engagement, highlighting the social dimension and influence of prominent figures in climate change information seeking. However, causal time series analyses show that events like these do not lead to long-lasting increased traffic.
Original language | English |
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Title of host publication | WebSci 2024 : Proceedings of the 16th ACM Web Science Conference |
Editors | Luca Maria Aiello, Yelena Mejova, Oshani Seneviratne, Jun Sun, Sierra Kaiser, Steffen Staab |
Number of pages | 11 |
Publisher | Association for Computing Machinery (ACM) |
Publication date | 21 May 2024 |
Pages | 365-375 |
ISBN (Electronic) | 979-8-4007-0334-8 |
DOIs | |
Publication status | Published - 21 May 2024 |
Event | 16th ACM Web Science Conference - Stuttgart, Germany Duration: 21 May 2024 → 24 May 2024 |
Conference
Conference | 16th ACM Web Science Conference |
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Country/Territory | Germany |
City | Stuttgart |
Period | 21/05/2024 → 24/05/2024 |
Keywords
- Climate Change
- Public Interest
- TIme Series Analysis
- Wikipedia