Project description
LLM impact on online peer production communities
Online peer production content communities, such as Wikipedia and GitHub, have long been vital internet hubs, offering users free access to knowledge and information. These communities have traditionally relied on active, voluntary contributions from dedicated members. However, the introduction of large language models (LLMs) has created unexpected uncertainties about their future. The ERC-funded LLMinPeerProduction project will examine the impact of LLMs on these communities, as well as the quality, type, and volume of contributions. It will also explore the potentially transformative effects of LLMs on user demand for content from these platforms. The project will use API-collected data and field experiments to carry out its analysis. Ultimately, the project will evaluate how LLMs reshape contributions and content demand.
Objective
This project explores the impact of generative AI technologies, specifically large language models (LLMs) on online peer production content communities, such as Wikipedia and GitHub. These communities depend heavily on the existence of a vibrant community and its members wiliness to contribute voluntarily and the introduction of LLM applications is expected to have transformative effect on the engagement dynamics within those production communities.
The proposal is structured around three primary aims: (1) the effects of LLM applications on individuals' willingness to engage and contribute to online communities, focusing on the quantity, type and quality of contributions; (2) the impact of LLM applications on communities openness, inclusiveness and trans-community mobility; and (3) the effects of LLM applications on users' demand for community-produced content, analyzing overall demand shifts and changes in content consumption patterns.
The project is based on an empirical analysis of publicly available data collected via APIs, as well as field experiments conducted in collaboration with existing online platforms. We are currently witnessing an explosion of new LLM applications over time, which are already disrupting various content communities and will contribute to do so during the lifetime of this project. We will collect longitudinal data on content communities in different domains and use the introduction of different LLM applications as quasi-experiments. We also present preliminary results, based on a quasi-experiment that leverages the selective rollout of GitHub Copilot, a ground-breaking coding-focused LLM, in October 2021.
This project is pivotal in gaining in-depth understanding of the evolving landscape of digital collaboration and content creation. It aims to provide actionable insights into the role of advanced LLM in shaping online communities, guiding future technological developments, policy-making, and community management strategies.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2024-COG
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69978 Tel Aviv
Israel
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