Grants:Programs/Wikimedia Research Fund/What lost elections tell us about the the supply of quality information on Wikipedia: A cross-country natural experiment
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Overview edit
Applicant(s)
- Giovanni Luca Ciampaglia and Ernesto Calvo
Affiliation or grant type
- University of Maryland
Author(s)
- Giovanni Luca Ciampaglia and Ernesto Calvo
Wikimedia username(s)
- Giovanni Luca Ciampaglia User:Junkie.dolphin
Ernesto Calvo
Project title
- What lost elections tell us about the the supply of quality information on Wikipedia: A cross-country natural experiment
Research proposal edit
Description edit
Description of the proposed project, including aims and approach. Be sure to clearly state the problem, why it is important, why previous approaches (if any) have been insufficient, and your methods to address it.
The research objective of this proposal is to investigate the role of online attention as a determinant of trustworthiness (i.e. information quality) of political knowledge on Wikipedia. Politics is one of the most consulted and edited topics in Wikipedia across languages, and while there is an extensive literature both on the link between online attention and political outcomes in different countries (e.g. election prediction), and between issue attention and quality information, less is known about the role of online attention in shaping the quality of political knowledge online. In prior work we have found that demand for information drives the creation of new Wikipedia articles, and that disinformation (in the form of hoax articles) is associated with spikes in attention, but the link between demand for information and information quality is still unclear. Can we measure the relationship between them? We propose a causal identification strategy to estimate the effect that attention shocks produce in the creation of quality content. Using data from the English, Spanish, and Italian editions of Wikipedia, we will focus on Wikipedia entries of incumbents who win or lose reelection by small margins, which are not yet sensitive to differences in endowments. We will consider members of the lower house of three national congresses: the US Congress, Argentina’s Cámara de Diputados de la Nación, and Italy’s Camera dei deputati. As the public's attention reacts to election results, we expect this discontinuity in attention to reward winners and to penalize losers, thus creating a natural experiment which allows us to study the effects of positive and negative attention shocks, endogenously determined by the election results, on a host of key determinants of information quality, such as the number of editors, the number of editing reversions, and the likelihood of vandalism. In the short term, we expect election results to alter the number of active editors, the number of editing reversions, the protected status of an account, the rate of vandalism, and, more generally, the overall quality of Wikipedia articles (measured via ORES). We will estimate heterogeneous effects by gender, ethnicity, and race in post-election edits, to determine if attention shocks affect majority and minority politicians differently.We also model long-term effects, as individuals that lose their reelection bids follow different career trajectories.
Personnel edit
- N/A
Budget edit
Approximate amount requested in USD.
- 50,000 USD
Budget Description
Briefly describe what you expect to spend money on (specific budgets and details are not necessary at this time).
1 week summer salary for both Pis + support 1 PhD student + Fringe:
$30,952
Travel:
$1,143
1x Computer laptop:
$1,500
Tuition remission (exempt from IDC):
$11,367
Total Direct Cost:
$44,961
Modified Total Direct Cost (MTDC):
$33,594
Indirect Costs (15% of MTDC):
$5,039
Impact edit
Address the impact and relevance to the Wikimedia projects, including the degree to which the research will address the 2030 Wikimedia Strategic Direction and/or support the work of Wikimedia user groups, affiliates, and developer communities. If your work relates to knowledge gaps, please directly relate it to the knowledge gaps taxonomy.
This research has two major potential impacts. First, it could help us better understand the role of Wikipedia in the political process in three countries (Argentina, Italy, and the USA) and could help us better understand why certain categories of politicians (like women or people of color) receive less attention from editors than others. Second, from the point of view of knowledge integrity, it could help us better understand the interplay of attention loss, individual interactions, and the production of information, which are all crucial factors in designing effective public policy and addressing power inequities in information networks in general. Finally, our focus on multiple languages could generalize to other cultures and projects.
Dissemination edit
Plans for dissemination.
We plan to pre-register our study on the OSF institutional repository and on Wikimedia’s meta wiki. We plan to publish 1–2 articles for the project described above. We will target venues such as CHI, CSCW, ICWSM, Nat. Comm, Nat. Hum. Beh., and Sci. Adv. We also have a track record of dissemination in the media (our research has been covered in the WSJ, NBC, NPR, SciAm, The Conversation, etc.). Finally, we will release all code from this research under an opensource license on Github or GitLab.
Past Contributions edit
Prior contributions to related academic and/or research projects and/or the Wikimedia and free culture communities. If you do not have prior experience, please explain your planned contributions.
We are both faculties at the University of Maryland. Giovanni is an expert in social computing with a decade-long history of research on Wikipedia and peer production communities, he has published articles on AfDs, MoodBar, editor retention, article creation, and Wikipedia hoaxes. He worked at the WMF as a summer intern and later as research analyst. Ernesto is an expert in political communication who has studied Congress, elections, social media, and news sharing in Latin America, Europe, and the United States. His current research focuses on topics of polarization, the partisan use of misinformation, fact checking interventions, and content sharing in social media. Our team has not been funded by the Wikimedia Research Fund before.
I agree to license the information I entered in this form excluding the pronouns, countries of residence, and email addresses under the terms of Creative Commons Attribution-ShareAlike 4.0. I understand that the decision to fund this Research Fund application, the application itself along with all the information entered by my in this form excluding the pronouns, country of residences, and email addresses of the personnel will be published on Wikimedia Foundation Funds pages on Meta-Wiki and will be made available to the public in perpetuity. To make the results of your research actionable and reusable by the Wikimedia volunteer communities, affiliates and Foundation, I agree that any output of my research will comply with the WMF Open Access Policy. I also confirm that I have read the privacy statement and agree to abide by the WMF Friendly Space Policy and Universal Code of Conduct.
- Yes