Title
Time-based tags for fiction movies: comparing experts to novices using a video labeling game.
Abstract
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.
Year
DOI
Venue
2017
10.1002/asi.23656
JASIST
Field
DocType
Volume
Data mining,World Wide Web,Information retrieval,Cultural heritage,Computer science,Crowdsourcing,Digital collections,Conceptual framework,Multimedia
Journal
68
Issue
ISSN
Citations 
2
2330-1635
0
PageRank 
References 
Authors
0.34
38
4
Name
Order
Citations
PageRank
Liliana Melgar Estrada100.34
Michiel Hildebrand231927.31
Victor de Boer318129.78
Jacco van Ossenbruggen481787.89