Limiting Tags Fosters Efficiency

Tiago Santos, Keith Burghardt, Kristina Lerman, Denis Helic

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


Tagging facilitates information retrieval in social media and other online communities by allowing users to organize and describe online content. Researchers found that the efficiency of tagging systems steadily decreases over time, because tags become less precise in identifying specific documents, i.e., they lose their descriptiveness. However, previous works did not answer how or even whether community managers can improve the efficiency of tags. In this work, we use information-theoretic measures to track the descriptive and retrieval efficiency of tags on Stack Overflow, a question-answering system that strictly limits the number of tags users can specify per question. We observe that tagging efficiency stabilizes over time, while tag content and descriptiveness both increase. To explain this observation, we hypothesize that limiting the number of tags fosters novelty and diversity in tag usage, two properties which are both beneficial for tagging efficiency. To provide qualitative evidence supporting our hypothesis, we present a statistical model of tagging that demonstrates how novelty and diversity lead to greater tag efficiency in the long run. Our work offers insights into policies to improve information organization and retrieval in online communities.

Original languageEnglish
Title of host publicationWebSci 2021 - Proceedings of the 13th ACM Web Science Conference
PublisherAssociation of Computing Machinery
Number of pages10
ISBN (Electronic)9781450383301
Publication statusPublished - 21 Jun 2021
Event13th ACM Web Science Conference: WebSci 2021 - Virtual, Online, United Kingdom
Duration: 21 Jun 202125 Jun 2021

Publication series

NameACM International Conference Proceeding Series


Conference13th ACM Web Science Conference
Country/TerritoryUnited Kingdom
CityVirtual, Online


  • information retrieval
  • social tagging
  • tag efficiency

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


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