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Time‐based tags for fiction movies: comparing experts to novices using a video labeling game
Author(s) -
Estrada Liliana Melgar,
Hildebrand Michiel,
de Boer Victor,
van Ossenbruggen Jacco
Publication year - 2017
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.23656
Subject(s) - crowdsourcing , computer science , cultural heritage , context (archaeology) , domain (mathematical analysis) , multimedia , similarity (geometry) , world wide web , quality (philosophy) , clips , data science , information retrieval , artificial intelligence , image (mathematics) , paleontology , mathematical analysis , philosophy , mathematics , archaeology , epistemology , biology , history
The cultural heritage sector has embraced social tagging as a way to increase both access to online content and to engage users with their digital collections. In this article, we build on two current lines of research. (a) We use Waisda? , an existing labeling game, to add time‐based annotations to content. (b) In this context, we investigate the role of experts in human‐based computation ( nichesourcing ). We report on a small‐scale experiment in which we applied Waisda? to content from film archives. We study the differences in the type of time‐based tags between experts and novices for film clips in a crowdsourcing setting. The findings show high similarity in the number and type of tags (mostly factual). In the less frequent tags, however, experts used more domain‐specific terms. We conclude that competitive games are not suited to elicit real expert‐level descriptions. We also confirm that providing guidelines, based on conceptual frameworks that are more suited to moving images in a time‐based fashion, could result in increasing the quality of the tags, thus allowing for creating more tag‐based innovative services for online audiovisual heritage.