Time‐based tags for fiction movies: comparing experts to novices using a video labeling game
研究通过视频标注游戏Waisda?，比较专家和新手为电影片段添加时间标签的差异，发现两者标签数量和类型高度相似，但专家更多使用专业术语。
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.