Wikipedia Article
Wikipedia articles are a rich source of data for studying various aspects of language, knowledge representation, and online communities. Current research focuses on leveraging Wikipedia's multilingual and structured nature to improve tasks like information retrieval, bias detection, and content moderation, often employing large language models (LLMs) and other machine learning techniques. These studies contribute to a deeper understanding of cross-cultural communication, the dynamics of online collaboration, and the challenges of maintaining high-quality information in a globally accessible encyclopedia. The resulting datasets and models have broad implications for computational social science, natural language processing, and the development of more robust and equitable online platforms.
Papers
A Test of Time: Predicting the Sustainable Success of Online Collaboration in Wikipedia
Abraham Israeli, David Jurgens, Daniel Romero
Language-Agnostic Modeling of Source Reliability on Wikipedia
Jacopo D'Ignazi, Andreas Kaltenbrunner, Yelena Mejova, Michele Tizzani, Kyriaki Kalimeri, Mariano Beiró, Pablo Aragón
Locating Information Gaps and Narrative Inconsistencies Across Languages: A Case Study of LGBT People Portrayals on Wikipedia
Farhan Samir, Chan Young Park, Anjalie Field, Vered Shwartz, Yulia Tsvetkov
Entity Insertion in Multilingual Linked Corpora: The Case of Wikipedia
Tomás Feith, Akhil Arora, Martin Gerlach, Debjit Paul, Robert West
HelloFresh: LLM Evaluations on Streams of Real-World Human Editorial Actions across X Community Notes and Wikipedia edits
Tim Franzmeyer, Aleksandar Shtedritski, Samuel Albanie, Philip Torr, João F. Henriques, Jakob N. Foerster
Linking Named Entities in Diderot's \textit{Encyclop\'edie} to Wikidata
Pierre Nugues