Folksonomies: Flickr image tagging: Patterns made visible

Beaudoin, Joan E.

doi:10.1002/bult.2007.1720340108

Cited by 33 publications

(30 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The study also confirms that abstract terms are rarely used when describing images (Balasubramanian et al, 2004;Beaudoin, 2007;Hollink et al, 2004;Jorgensen, 1996). The most commonly occurring image facets identified in the tags in this study were people and objects (Who facet), followed by locations (Where facet).…”

Section: Discussionsupporting

confidence: 84%

Facets of user‐assigned tags and their effectiveness in image retrieval

Ransom

Rafferty²

2011

Journal of Documentation

View full text Add to dashboard Cite

Purpose -This study aims to consider the value of user-assigned image tags by comparing the facets that are represented in image tags with those that are present in image queries to see if there is a similarity in the way that users describe and search for images. Design/methodology/approach -A sample dataset was created by downloading a selection of images and associated tags from Flickr, the online photo-sharing web site. The tags were categorised using image facets from Shatford's matrix, which has been widely used in previous research into image indexing and retrieval. The facets present in the image tags were then compared with the results of previous research into image queries. Findings -The results reveal that there are broad similarities between the facets present in image tags and queries, with people and objects being the most common facet, followed by location. However, the results also show that there are differences in the level of specificity between tags and queries, with image tags containing more generic terms and image queries consisting of more specific terms. The study concludes that users do describe and search for images using similar image facets, but that measures to close the gap between specific queries and generic tags would improve the value of user tags in indexing image collections. Originality/value -Research into tagging has tended to focus on textual resources with less research into non-textual documents. In particular, little research has been undertaken into how user tags compare to the terms used in search queries, particularly in the context of digital images.

show abstract

Section: Discussionsupporting

confidence: 84%

Facets of user‐assigned tags and their effectiveness in image retrieval

Ransom

Rafferty²

2011

Journal of Documentation

View full text Add to dashboard Cite

show abstract

“…Flickr is a source of wonderment for those wishing to study user-generated content and large-scale online communities (Negoescu & Gatica-Perez, 2008); how and why individuals build up their own image-based collections (Stvilia & Jörgensen, 2007;Stvilia & Jörgensen, 2009); how users are interacting with media in the changing information environment; and how digital media and online content is changing society (Van House, 2007). Within the computing science, library, and archive communities, there has been much interest in the use of tags-user generated descriptions of images that can be used as a crude form of metadata, to enable labelling, searching, and retrieving-and how these can be used to generate automated systems or to understand users further (Angus, Thelwall, & Stuart 2008;Beaudoin, 2007;Marlow, Naaman, Boyd, & David, 2006;Morrison, 2007;Nov, Narman, & Ye, 2008;Rafferty & Hidderly, 2007;Trant, 2009). There have been few qualitative studies, however, on the motivations of specific user communities in providing their own digitized content rather than tagging existing materials.…”

Section: The Growth Of Flickrmentioning

confidence: 99%

The Digital Wunderkammer: Flickr as a Platform for Amateur Cultural and Heritage Content

Terras¹

2011

lib

View full text Add to dashboard Cite

Many memory institutions are now digitizing their holdings to provide online access. Although recent developments in technology have allowed users to create high quality digital resources outside institutional boundaries, little consideration has been given to the potential contribution that the general public can make to digitizing cultural heritage. This article seeks to scope the growing trend of the creation of digital images of cultural and heritage materials beyond library, art gallery, or museum walls, particularly focusing on the use of the image-hosting site Flickr (www.flickr.com) as a forum for hosting, discussing, and collecting vintage ephemera. This article discusses how Flickr is currently being used and provides empirical data that demonstrates that the most successful examples of this approach can teach best practice to traditional memory institutions in how to make their collections useful, interesting, and used by online communities. The use of a common, centralized access point to image-based heritage allows a central point for discussing and accessing collections. Furthermore, the adoption of Flickr by libraries and archives can extend the use of collections and the interaction that this affords both the institution and the individual.

show abstract

“…As suggested by Beaudoin (2007) as well as by Bolognesi (2016), Flickr tags encode primarily semantic information about the situational properties of a given concept. In fact, given a tag X, the tags that typically appear together with X across Flickr pictures express on average locations and related entities that can be found in the same context (i.e., within the same picture).…”

Section: Methodsmentioning

confidence: 99%

“…This source of data contains spontaneous annotations of personal pictures, which are not suggested by the Flickr platform. The information encoded in Flickr tags has been classified by Beaudoin (2007) in 18 post hoc created categories, which include syntactic property types (e.g., adjectives, verbs), semantic classes (human participants, living things other than humans, non-living things), places, events/activities (e.g., wedding, Christmas, holidays), ad hoc created categories (such as photographic vocabulary, e.g., macro, Nikon), emotions, formal classifications such as terms written in any language other than English, and compound terms written as one word (e.g., mydog). Of all the 18 types of tags identified, Beaudoin reports that the most frequent are (i) geographical locations, (ii) compounds, (iii) inanimate objects, (iv) participants, and (v) events.…”

mentioning

confidence: 99%

Modeling Semantic Similarity between Metaphor Terms of Visual vs. Linguistic Metaphors through Flickr Tag Distributions

Bolognesi

2016

Front. Commun.

View full text Add to dashboard Cite

This study aims at modeling the semantic similarity between metaphor terms by means of a distributional method based on a Big Data stream: Flickr tags. As explained in the article, this distributional model, Flickr Distributional Tagspace (FDT), captures primarily relational similarity between concept pairs, that is, between tags that appear in similar tagsets (and therefore in similar pictures). A long established view in metaphor theory claims that metaphors pertain to the conceptual dimension of meaning, but while different models aim at explaining how language constructs and represents metaphorical conceptual structures, we still know very little about how other modalities (for example, images) achieve metaphor construction and expression. A comprehensive theory, which argues in favor of the conceptual nature of metaphor, cannot afford to be biased toward the analysis and modeling of one specific modality of expression, thus neglecting potential modalityspecific differences. The present study, conducted through FDT, found that visual and linguistic metaphors behave differently, in that the similarity between two aligned concepts in a visual metaphor appears to be significantly higher than the similarity between two concepts aligned in a linguistic metaphor (which, in turn, does not differ substantially from the similarity between two randomly paired concepts). These findings suggest that the relational similarity between two metaphor terms (captured and modeled through FDT) is crucial for visual metaphors but not for linguistic metaphors. An additional content analysis, also reported here, shows that the type of semantic information encoded in the related tags (i.e., the contexts on which the contingency matrices of this distributional method are built) differs, in relation to the modality of the metaphor: while situationrelated and entity-related features are typically associated with concepts aligned in visual metaphors, introspections, and taxonomic features are typically associated with concepts aligned in linguistic metaphors. INTRODUCTIONMetaphor is recognized nowadays as a cognitive mechanism, rather than a simple figure of speech (Lakoff and Johnson, 1980;Lakoff, 1993). Through metaphors, we understand one concept in terms of another concept, the latter being generally perceived as easier or more concrete. On this view, metaphoric expressions, such as our love is at a crossroads, we can't turn back now, together we are not going anywhere, suggest that when we deal with the abstract concept of LOVE (by convention, capital letters are used when referring to a concept or a conceptual domain), we might somehow envision a concrete journey going along a path. This conceptualization allows us to extend the metaphor, and imagine the two lovers as two travelers, the difficulties in the relationship as impediments on the journey, and the lovers' goals as the travel destination. From this complex and rather subconscious conceptual structure (LOVE-IS-JOURNEY), we would then derive metaphoric linguistic expressi...

show abstract

Folksonomies: Flickr image tagging: Patterns made visible

Cited by 33 publications

References 0 publications

Facets of user‐assigned tags and their effectiveness in image retrieval

Facets of user‐assigned tags and their effectiveness in image retrieval

The Digital Wunderkammer: Flickr as a Platform for Amateur Cultural and Heritage Content

Modeling Semantic Similarity between Metaphor Terms of Visual vs. Linguistic Metaphors through Flickr Tag Distributions

Contact Info

Product

Resources

About