Fun Facts: Automatic Trivia Fact Extraction from Wikipedia
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Abstract (arXiv)
A significant portion of web search queries directly refers to named entities. Search engines explore various ways to improve the user experience for such queries. We suggest augmenting search results with em trivia facts about the searched entity. Trivia is widely played throughout the world, and was shown to increase users' engagement and retention. Most random facts are not suitable for the trivia section. There is skill (and art) to curating good trivia. In this paper, we formalize a notion of trivia-worthiness and propose an algorithm that automatically mines trivia facts from Wikipedia. We take advantage of Wikipedia's category structure, and rank an entity's categories by their trivia-quality. Our algorithm is capable of finding interesting facts, such as Obama's Grammy or Elvis' stint as a tank gunner. In user studies, our algorithm captures the intuitive notion of "good trivia" 45% higher than prior work. Search-page tests show a 22% decrease in bounce rates and a 12% increase in dwell time, proving our facts hold users' attention.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Dec 2016.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 0; 2025: 1.
3 papers.
- 2021What's the best place for an AI conference, Vancouver or ______: Why completing comparative questions is difficultcited by 4
- 2022Semantic Novelty Detection and Characterization in Factual Text Involving Named Entitiescited by 0
- 2025Wikipedia-based Datasets in Russian Information Retrieval Benchmark RusBEIRcited by 0
- 2025Wikipedia-based Datasets in Russian Information Retrieval Benchmark RusBEIR7 Nov 2025
- 2022Semantic Novelty Detection and Characterization in Factual Text Involving Named Entities31 Oct 2022
- 2021What's the best place for an AI conference, Vancouver or ______: Why completing comparative questions is difficult5 Apr 2021