Search (31 results, page 1 of 2)

  • × theme_ss:"Social tagging"
  • × year_i:[2010 TO 2020}
  1. Chan, L.M.: Social bookmarking and subject indexing (2011) 0.05
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    Series
    IFLA series on bibliographic control; vol. 42
    Source
    Subject access: preparing for the future. Conference on August 20 - 21, 2009 in Florence, the IFLA Classification and Indexing Section sponsored an IFLA satellite conference entitled "Looking at the Past and Preparing for the Future". Eds.: P. Landry et al
  2. Aagaard, H.: Social indexing at the Stockholm Public Library (2011) 0.05
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    Series
    IFLA series on bibliographic control; vol. 42
    Source
    Subject access: preparing for the future. Conference on August 20 - 21, 2009 in Florence, the IFLA Classification and Indexing Section sponsored an IFLA satellite conference entitled "Looking at the Past and Preparing for the Future". Eds.: P. Landry et al
  3. Bundza, M.: ¬The choice is yours! : researchers assign subject metadata to their own materials in institutional repositories (2014) 0.02
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    Abstract
    The Digital Commons platform for institutional repositories provides a three-tiered taxonomy of academic disciplines for each item submitted to the repository. Since faculty and departmental administrators across campuses are encouraged to submit materials to the institutional repository themselves, they must also assign disciplines or subject categories for their own work. The expandable drop-down menu of about 1,000 categories is easy to use, and facilitates the growth of the institutional repository and access to the materials through the Internet.
    Footnote
    Contribution in a special issue "Beyond libraries: Subject metadata in the digital environment and Semantic Web" - Enthält Beiträge der gleichnamigen IFLA Satellite Post-Conference, 17-18 August 2012, Tallinn.
    Source
    Cataloging and classification quarterly. 52(2014) no.1, S.110-118
  4. Golub, K.; Lykke, M.; Tudhope, D.: Enhancing social tagging with automated keywords from the Dewey Decimal Classification (2014) 0.02
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    Abstract
    Purpose - The purpose of this paper is to explore the potential of applying the Dewey Decimal Classification (DDC) as an established knowledge organization system (KOS) for enhancing social tagging, with the ultimate purpose of improving subject indexing and information retrieval. Design/methodology/approach - Over 11.000 Intute metadata records in politics were used. Totally, 28 politics students were each given four tasks, in which a total of 60 resources were tagged in two different configurations, one with uncontrolled social tags only and another with uncontrolled social tags as well as suggestions from a controlled vocabulary. The controlled vocabulary was DDC comprising also mappings from the Library of Congress Subject Headings. Findings - The results demonstrate the importance of controlled vocabulary suggestions for indexing and retrieval: to help produce ideas of which tags to use, to make it easier to find focus for the tagging, to ensure consistency and to increase the number of access points in retrieval. The value and usefulness of the suggestions proved to be dependent on the quality of the suggestions, both as to conceptual relevance to the user and as to appropriateness of the terminology. Originality/value - No research has investigated the enhancement of social tagging with suggestions from the DDC, an established KOS, in a user trial, comparing social tagging only and social tagging enhanced with the suggestions. This paper is a final reflection on all aspects of the study.
  5. Matthews, B.; Jones, C.; Puzon, B.; Moon, J.; Tudhope, D.; Golub, K.; Nielsen, M.L.: ¬An evaluation of enhancing social tagging with a knowledge organization system (2010) 0.02
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    Abstract
    Purpose - Traditional subject indexing and classification are considered infeasible in many digital collections. This paper seeks to investigate ways of enhancing social tagging via knowledge organization systems, with a view to improving the quality of tags for increased information discovery and retrieval performance. Design/methodology/approach - Enhanced tagging interfaces were developed for exemplar online repositories, and trials were undertaken with author and reader groups to evaluate the effectiveness of tagging augmented with control vocabulary for subject indexing of papers in online repositories. Findings - The results showed that using a knowledge organisation system to augment tagging does appear to increase the effectiveness of non-specialist users (that is, without information science training) in subject indexing. Research limitations/implications - While limited by the size and scope of the trials undertaken, these results do point to the usefulness of a mixed approach in supporting the subject indexing of online resources. Originality/value - The value of this work is as a guide to future developments in the practical support for resource indexing in online repositories.
  6. Choi, Y.: ¬A Practical application of FRBR for organizing information in digital environments (2012) 0.01
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    Abstract
    This study employs the FRBR (Functional Requirements for Bibliographic Records) conceptual model to provide in-depth investigation on the characteristics of social tags by analyzing the bibliographic attributes of tags that are not limited to subject properties. FRBR describes four different levels of entities (i.e., Work, Expression, Manifestation, and Item), which provide a distinguishing understanding of each entity in the bibliographic universe. In this research, since the scope of data analysis focuses on tags assigned to web documents, consideration on Manifestation and Item has been excluded. Accordingly, only the attributes of Work and Expression entity were investigated in order to map the attributes of tags to attributes defined in those entities. The content analysis on tag attributes was conducted on a total of 113 web documents regarding 11 attribute categories defined by FRBR. The findings identified essential bibliographic attributes of tags and tagging behaviors by subject. The findings showed that concerning specific subject areas, taggers exhibited different tagging behaviors representing distinctive features and tendencies. These results have led to the conclusion that there should be an increased awareness of diverse user needs by subject in terms of the practical implications of metadata generation.
  7. Huang, C.; Fu, T.; Chen, H.: Text-based video content classification for online video-sharing sites (2010) 0.01
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    Abstract
    With the emergence of Web 2.0, sharing personal content, communicating ideas, and interacting with other online users in Web 2.0 communities have become daily routines for online users. User-generated data from Web 2.0 sites provide rich personal information (e.g., personal preferences and interests) and can be utilized to obtain insight about cyber communities and their social networks. Many studies have focused on leveraging user-generated information to analyze blogs and forums, but few studies have applied this approach to video-sharing Web sites. In this study, we propose a text-based framework for video content classification of online-video sharing Web sites. Different types of user-generated data (e.g., titles, descriptions, and comments) were used as proxies for online videos, and three types of text features (lexical, syntactic, and content-specific features) were extracted. Three feature-based classification techniques (C4.5, Naïve Bayes, and Support Vector Machine) were used to classify videos. To evaluate the proposed framework, user-generated data from candidate videos, which were identified by searching user-given keywords on YouTube, were first collected. Then, a subset of the collected data was randomly selected and manually tagged by users as our experiment data. The experimental results showed that the proposed approach was able to classify online videos based on users' interests with accuracy rates up to 87.2%, and all three types of text features contributed to discriminating videos. Support Vector Machine outperformed C4.5 and Naïve Bayes techniques in our experiments. In addition, our case study further demonstrated that accurate video-classification results are very useful for identifying implicit cyber communities on video-sharing Web sites.
  8. Spiteri, L.F.: Incorporating facets into social tagging applications : an analysis of current trends (2010) 0.01
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    Source
    Cataloging and classification quarterly. 48(2010) no.1, S.94-109
  9. Watters, C.; Nizam, N.: Knowledge organization on the Web : the emergent role of social classification (2012) 0.01
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  10. Wang, Y.; Tai, Y.; Yang, Y.: Determination of semantic types of tags in social tagging systems (2018) 0.01
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    Abstract
    The purpose of this paper is to determine semantic types for tags in social tagging systems. In social tagging systems, the determination of the semantic type of tags plays an important role in tag classification, increasing the semantic information of tags and establishing mapping relations between tagged resources and a normed ontology. The research reported in this paper constructs the semantic type library that is needed based on the Unified Medical Language System (UMLS) and FrameNet and determines the semantic type of selected tags that have been pretreated via direct matching using the Semantic Navigator tool, the Semantic Type Word Sense Disambiguation (STWSD) tools in UMLS, and artificial matching. And finally, we verify the feasibility of the determination of semantic type for tags by empirical analysis.
  11. Choi, Y.; Syn, S.Y.: Characteristics of tagging behavior in digitized humanities online collections (2016) 0.01
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    Abstract
    The purpose of this study was to examine user tags that describe digitized archival collections in the field of humanities. A collection of 8,310 tags from a digital portal (Nineteenth-Century Electronic Scholarship, NINES) was analyzed to find out what attributes of primary historical resources users described with tags. Tags were categorized to identify which tags describe the content of the resource, the resource itself, and subjective aspects (e.g., usage or emotion). The study's findings revealed that over half were content-related; tags representing opinion, usage context, or self-reference, however, reflected only a small percentage. The study further found that terms related to genre or physical format of a resource were frequently used in describing primary archival resources. It was also learned that nontextual resources had lower numbers of content-related tags and higher numbers of document-related tags than textual resources and bibliographic materials; moreover, textual resources tended to have more user-context-related tags than other resources. These findings help explain users' tagging behavior and resource interpretation in primary resources in the humanities. Such information provided through tags helps information professionals decide to what extent indexing archival and cultural resources should be done for resource description and discovery, and understand users' terminology.
    Date
    21. 4.2016 11:23:22
  12. Chae, G.; Park, J.; Park, J.; Yeo, W.S.; Shi, C.: Linking and clustering artworks using social tags : revitalizing crowd-sourced information on cultural collections (2016) 0.00
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    Abstract
    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 crowd-sourced 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.
  13. Lee, Y.Y.; Yang, S.Q.: Folksonomies as subject access : a survey of tagging in library online catalogs and discovery layers (2012) 0.00
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    Abstract
    This paper describes a survey on how system vendors and libraries handled tagging in OPACs and discovery layers. Tags are user added subject metadata, also called folksonomies. This survey also investigated user behavior when they face the possibility to tag. The findings indicate that legacy/classic systems have no tagging capability. About 47% of the discovery tools provide tagging function. About 49% of the libraries that have a system with tagging capability have turned the tagging function on in their OPACs and discovery tools. Only 40% of the libraries that turned tagging on actually utilized user added subject metadata as access point to collections. Academic library users are less active in tagging than public library users.
    Source
    Beyond libraries - subject metadata in the digital environment and semantic web. IFLA Satellite Post-Conference, 17-18 August 2012, Tallinn
  14. Yi, K.: ¬A semantic similarity approach to predicting Library of Congress subject headings for social tags (2010) 0.00
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    Abstract
    Social tagging or collaborative tagging has become a new trend in the organization, management, and discovery of digital information. The rapid growth of shared information mostly controlled by social tags poses a new challenge for social tag-based information organization and retrieval. A plausible approach for this challenge is linking social tags to a controlled vocabulary. As an introductory step for this approach, this study investigates ways of predicting relevant subject headings for resources from social tags assigned to the resources. The prediction of subject headings was measured by five different similarity measures: tf-idf, cosine-based similarity (CoS), Jaccard similarity (or Jaccard coefficient; JS), Mutual information (MI), and information radius (IRad). Their results were compared to those by professionals. The results show that a CoS measure based on top five social tags was most effective. Inclusions of more social tags only aggravate the performance. The performance of JS is comparable to the performance of CoS while tf-idf is comparable with up to 70% less than the best performance. MI and IRad have inferior performance compared to the other methods. This study demonstrates the application of the similarity measuring techniques to the prediction of correct Library of Congress subject headings.
  15. Evedove Tartarotti, R. Dal'; Lopes Fujita, M.: ¬The perspective of social indexing in online bibliographic catalogs : between the individual and the collaborative (2016) 0.00
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  16. Kipp, M.E.I.; Campbell, D.G.: Searching with tags : do tags help users find things? (2010) 0.00
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    Abstract
    The question of whether tags can be useful in the process of information retrieval was examined in this pilot study. Many tags are subject related and could work well as index terms or entry vocabulary; however, folksonomies also include relationships that are traditionally not included in controlled vocabularies including affective or time and task related tags and the user name of the tagger. Participants searched a social bookmarking tool, specialising in academic articles (CiteULike), and an online journal database (Pubmed) for articles relevant to a given information request. Screen capture software was used to collect participant actions and a semi-structured interview asked them to describe their search process. Preliminary results showed that participants did use tags in their search process, as a guide to searching and as hyperlinks to potentially useful articles. However, participants also used controlled vocabularies in the journal database to locate useful search terms and links to related articles supplied by Pubmed. Additionally, participants reported using user names of taggers and group names to help select resources by relevance. The inclusion of subjective and social information from the taggers is very different from the traditional objectivity of indexing and was reported as an asset by a number of participants. This study suggests that while users value social and subjective factors when searching, they also find utility in objective factors such as subject headings. Most importantly, users are interested in the ability of systems to connect them with related articles whether via subject access or other means.
  17. Kipp, M.E.I.: Tagging of biomedical articles on CiteULike : a comparison of user, author and professional indexing (2011) 0.00
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    Abstract
    This paper examines the context of online indexing from the viewpoint of three different groups: users, authors, and professional indexers. User tags, author keywords, and descriptors were collected from academic journal articles, which were both indexed in PubMed and tagged on CiteULike, and analysed. Descriptive statistics, informetric measures, and thesaural term comparison shows that there are important differences in the use of keywords among the three groups in addition to similarities, which can be used to enhance support for search and browse. While tags and author keywords were found that matched descriptors exactly, other terms which did not match but provided important expansion to the indexing lexicon were found. These additional terms could be used to enhance support for searching and browsing in article databases as well as to provide invaluable data for entry vocabulary and emergent terminology for regular updates to indexing systems. Additionally, the study suggests that tags support organisation by association to task, projects, and subject while making important connections to traditional systems which classify into subject categories.
  18. Vaidya, P.; Harinarayana, N.S.: ¬The comparative and analytical study of LibraryThing tags with Library of Congress Subject Headings (2016) 0.00
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    Abstract
    The internet in its Web 2.0 version has given an opportunity among users to be participative and the chance to enhance the existing system, which makes it dynamic and collaborative. The activity of social tagging among researchers to organize the digital resources is an interesting study among information professionals. The one way of organizing the resources for future retrieval through these user-generated terms makes an interesting analysis by comparing them with professionally created controlled vocabularies. Here in this study, an attempt has been made to compare Library of Congress Subject Headings (LCSH) terms with LibraryThing social tags. In this comparative analysis, the results show that social tags can be used to enhance the metadata for information retrieval. But still, the uncontrolled nature of social tags is a concern and creates uncertainty among researchers.
  19. Lee, D.H.; Schleyer, T.: Social tagging is no substitute for controlled indexing : a comparison of Medical Subject Headings and CiteULike tags assigned to 231,388 papers (2012) 0.00
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    Abstract
    Social tagging and controlled indexing both facilitate access to information resources. Given the increasing popularity of social tagging and the limitations of controlled indexing (primarily cost and scalability), it is reasonable to investigate to what degree social tagging could substitute for controlled indexing. In this study, we compared CiteULike tags to Medical Subject Headings (MeSH) terms for 231,388 citations indexed in MEDLINE. In addition to descriptive analyses of the data sets, we present a paper-by-paper analysis of tags and MeSH terms: the number of common annotations, Jaccard similarity, and coverage ratio. In the analysis, we apply three increasingly progressive levels of text processing, ranging from normalization to stemming, to reduce the impact of lexical differences. Annotations of our corpus consisted of over 76,968 distinct tags and 21,129 distinct MeSH terms. The top 20 tags/MeSH terms showed little direct overlap. On a paper-by-paper basis, the number of common annotations ranged from 0.29 to 0.5 and the Jaccard similarity from 2.12% to 3.3% using increased levels of text processing. At most, 77,834 citations (33.6%) shared at least one annotation. Our results show that CiteULike tags and MeSH terms are quite distinct lexically, reflecting different viewpoints/processes between social tagging and controlled indexing.
  20. Ding, Y.; Jacob, E.K.; Fried, M.; Toma, I.; Yan, E.; Foo, S.; Milojevicacute, S.: Upper tag ontology for integrating social tagging data (2010) 0.00
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    Abstract
    Data integration and mediation have become central concerns of information technology over the past few decades. With the advent of the Web and the rapid increases in the amount of data and the number of Web documents and users, researchers have focused on enhancing the interoperability of data through the development of metadata schemes. Other researchers have looked to the wealth of metadata generated by bookmarking sites on the Social Web. While several existing ontologies have capitalized on the semantics of metadata created by tagging activities, the Upper Tag Ontology (UTO) emphasizes the structure of tagging activities to facilitate modeling of tagging data and the integration of data from different bookmarking sites as well as the alignment of tagging ontologies. UTO is described and its utility in modeling, harvesting, integrating, searching, and analyzing data is demonstrated with metadata harvested from three major social tagging systems (Delicious, Flickr, and YouTube).