Structured versus unstructured tagging: a case study

Bar‐Ilan, Judit; Shoham, Snunith; Idan, Asher; Miller, Yitzchak; Shachak, Aviv

doi:10.1108/14684520810914016

Cited by 45 publications

(35 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This undermines the role of social tags as a meaningful bridge (Smith, 2006). Bar-Ilan, Shoham, Idan, Miller, and Shachak (2008) proposed that structured tags can help overcome these limitations by facilitating a deeper understanding about contents compared to the conventional tag cloud, which is an unstructured set of tags. Hearst (2006) also wrote that structured tags allow users to understand better the relationships between tags and make a quicker decision about how to use this information.…”

Section: Social Tagging Systems For Artworkmentioning

confidence: 98%

Linking and clustering artworks using social tags: Revitalizing crowd‐sourced information on cultural collections

Chae

Park

et al. 2015

Asso for Info Science & Tech

View full text Add to dashboard Cite

Social tagging is one of the most popular methods for collecting crowd-sourced information in galleries, libraries, archives, and museums (GLAMs). However, when the number of social tags grows rapidly, using them becomes problematic and, as a result, they are often left as simply big data that cannot be used for practical purposes. To revitalize the use of this crowdsourced information, we propose using social tags to link and cluster artworks based on an experimental study using an online collection at the Gyeonggi Museum of Modern Art (GMoMA). We view social tagging as a folksonomy, where artworks are classified by keywords of the crowd's various interpretations and one artwork can belong to several different categories simultaneously. To leverage this strength of social tags, we used a clustering method called "link communities" to detect overlapping communities in a network of artworks constructed by computing similarities between all artwork pairs. We used this framework to identify semantic relationships and clusters of similar artworks. By comparing the clustering results with curators' manual classification results, we demonstrated the potential of social tagging data for automatically clustering artworks in a way that reflects the dynamic perspectives of crowds.

show abstract

Section: Social Tagging Systems For Artworkmentioning

confidence: 98%

Linking and clustering artworks using social tags: Revitalizing crowd‐sourced information on cultural collections

Chae

Park

et al. 2015

Asso for Info Science & Tech

View full text Add to dashboard Cite

show abstract

“…Many studies have shown that, although professionals cannot be replaced, social tags enhance the description of images for users and provide data useful for retrieval. Bar-Ilan, Shoham, Idan, Miller, and Shachak (2008) found that for image retrieval, structured tagging done by professionals remains the best method for successful retrieval. However, credence should be paid to social tagging (Unstructured tagging) as it allows for a wider range of tags that may prove more useful in completing successful queries.…”

Section: Related Workmentioning

confidence: 98%

An experimental study of social tagging behavior and image content

Golbeck

Koepfler

Emmerling

2011

J. Am. Soc. Inf. Sci.

View full text Add to dashboard Cite

Social tags have become an important tool for improving access to online resources, particularly non-text media. With the dramatic growth of user-generated content, the importance of tags is likely to grow. However, while tagging behavior is well studied, the relationship between tagging behavior and features of the media being tagged is not well understood. In this paper, we examine the relationship between tagging behavior and image type. Through a lab-based study with 51 subjects and an analysis of an online dataset of image tags, we show that there are significant differences in the number, order, and type of tags that users assign based on their past experience with an image, the type of image being tagged, and other image features. We present these results and discuss the significant implications this work has for tagbased search algorithms, tag recommendation systems, and other interface issues.

show abstract

“…Wolfram, Olson, and Bloom (2009) emphasized the importance of this sort of work when they stated that "it is worthwhile to explore potential parallel characteristics between indexing and tagging as these characteristics could influence the form of tagging offered in a given situation and how tagging influences retrieval" (p. 1996) and called for a better understanding of the nature of tags. Others (Bar-Ilan, Shoham, Idan, Miller, & Shachak, 2008) have also called for studies on the strengths and shortcomings of tags and conventional indexing methods. To clearly define the research problem, a review of the phenomenon of social tagging and literature on indexing in general and image indexing in particular is necessary.…”

Section: Introductionmentioning

confidence: 99%

A comparative study of Flickr tags and index terms in a general image collection

Rorissa

2010

J. Am. Soc. Inf. Sci.

View full text Add to dashboard Cite

Web 2.0 and social/collaborative tagging have altered the traditional roles of indexer and user. Traditional indexing tools and systems assume the top-down approach to indexing in which a trained professional is responsible for assigning index terms to information sources with a potential user in mind. However, in today's Web, end users create, organize, index, and search for images and other information sources through social tagging and other collaborative activities. One of the impediments to user-centered indexing had been the cost of soliciting user-generated index terms or tags. Social tagging of images such as those on Flickr, an online photo management and sharing application, presents an opportunity that can be seized by designers of indexing tools and systems to bridge the semantic gap between indexer terms and user vocabularies. Empirical research on the differences and similarities between user-generated tags and index terms based on controlled vocabularies has the potential to inform future design of image indexing tools and systems.Toward this end, a random sample of Flickr images and the tags assigned to them were content analyzed and compared with another sample of index terms from a general image collection using established frameworks for image attributes and contents. The results show that there is a fundamental difference between the types of tags and types of index terms used. In light of this, implications for research into and design of user-centered image indexing tools and systems are discussed.

show abstract

Structured versus unstructured tagging: a case study

Cited by 45 publications

References 10 publications

Linking and clustering artworks using social tags: Revitalizing crowd‐sourced information on cultural collections

Linking and clustering artworks using social tags: Revitalizing crowd‐sourced information on cultural collections

An experimental study of social tagging behavior and image content

A comparative study of Flickr tags and index terms in a general image collection

Contact Info

Product

Resources

About