Search (3275 results, page 2 of 164)

0.09619903 = product of:
  0.19239806 = sum of:
    0.19239806 = product of:
      0.3847961 = sum of:
        0.3847961 = weight(_text_:tagging in 2891) [ClassicSimilarity], result of:
          0.3847961 = score(doc=2891,freq=16.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.2914723 = fieldWeight in 2891, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2891)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Social-Tagging-Systeme bieten eine Vielzahl an Vorteilen gegenüber traditionellen und zurzeit eingesetzten Systemen und werden besonders in nicht-kommerziellen Web-2.0-Anwendungen erfolgreich verwendet. Diese Arbeit beschäftigt sich mit den Vor- und Nachteilen von Social Tagging für kollaborative Systeme des Electronic Commerce und stellt einige Beispiele aus der Praxis vor. Es gibt nur wenige Anwendungen aus dem Bereich des Electronic Commerce, die Social Tagging erfolgreich als kritischen Teil ihrer Systeme einsetzen. Deshalb wird das Potenzial von Tagging-Systemen beleuchtet, um eine fundierte Basis für neue Entwicklungen im Geschäftsbereich zu schaffen.

Footnote

Beitrag der Tagung "Social Tagging in der Wissensorganisation" am 21.-22.02.2008 am Institut für Wissensmedien (IWM) in Tübingen.

Source

Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a

Theme

Social tagging

0.08745811 = product of:
  0.17491622 = sum of:
    0.17491622 = product of:
      0.34983245 = sum of:
        0.34983245 = weight(_text_:tagging in 3290) [ClassicSimilarity], result of:
          0.34983245 = score(doc=3290,freq=18.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.1741256 = fieldWeight in 3290, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.046875 = fieldNorm(doc=3290)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Social tagging is one of the major phenomena transforming the World Wide Web from a static platform into an actively shared information space. This paper addresses various aspects of social tagging, including different views on the nature of social tagging, how to make use of social tags, and how to bridge social tagging with other Web functionalities; it discusses the use of facets to facilitate browsing and searching of tagging data; and it presents an analogy between bibliometrics and tagometrics, arguing that established bibliometric methodologies can be applied to analyze tagging behavior on the Web. Based on the Upper Tag Ontology (UTO), a Web crawler was built to harvest tag data from Delicious, Flickr, and YouTube in September 2007. In total, 1.8 million objects, including bookmarks, photos, and videos, 3.1 million taggers, and 12.1 million tags were collected and analyzed. Some tagging patterns and variations are identified and discussed.

Theme

Social tagging

0.08745811 = product of:
  0.17491622 = sum of:
    0.17491622 = product of:
      0.34983245 = sum of:
        0.34983245 = weight(_text_:tagging in 309) [ClassicSimilarity], result of:
          0.34983245 = score(doc=309,freq=18.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.1741256 = fieldWeight in 309, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.046875 = fieldNorm(doc=309)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

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.

Theme

Social tagging

0.08691658 = product of:
  0.17383316 = sum of:
    0.17383316 = product of:
      0.34766632 = sum of:
        0.34766632 = weight(_text_:tagging in 2886) [ClassicSimilarity], result of:
          0.34766632 = score(doc=2886,freq=10.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.1668555 = fieldWeight in 2886, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0625 = fieldNorm(doc=2886)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Der vorliegende Artikel beleuchtet die Perspektiven und Grenzen der Einführung von partizipatorischen Elementen in die traditionelle bibliothekarische Sacherschließung. Die Universitätsbibliothek Mannheim untersucht im vorgestellten Projekt, welchen Beitrag Collaborative Tagging für die inhaltliche Erschließung von bisher nicht erschlossenen und daher der Nutzung kaum zugänglichen Dokumenten, beispielsweise auf Volltextservern oder in elektronischen Zeitschriften, leisten kann.

Footnote

Beitrag der Tagung "Social Tagging in der Wissensorganisation" am 21.-22.02.2008 am Institut für Wissensmedien (IWM) in Tübingen.

Source

Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a

Theme

Social tagging

0.085807584 = product of:
  0.17161517 = sum of:
    0.17161517 = sum of:
      0.13742718 = weight(_text_:tagging in 2648) [ClassicSimilarity], result of:
        0.13742718 = score(doc=2648,freq=4.0), product of:
          0.2979515 = queryWeight, product of:
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.05046712 = queryNorm
          0.4612401 = fieldWeight in 2648, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2648)
      0.03418799 = weight(_text_:22 in 2648) [ClassicSimilarity], result of:
        0.03418799 = score(doc=2648,freq=2.0), product of:
          0.17672725 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.05046712 = queryNorm
          0.19345059 = fieldWeight in 2648, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2648)
  0.5 = coord(1/2)

Abstract

The growing predominance of social semantics in the form of tagging presents the metadata community with both opportunities and challenges as for leveraging this new form of information content representation and for retrieval. One key challenge is the absence of contextual information associated with these tags. This paper presents an experiment working with Flickr tags as an example of utilizing social semantics sources for enriching subject metadata. The procedure included four steps: 1) Collecting a sample of Flickr tags, 2) Calculating cooccurrences between tags through mutual information, 3) Tracing contextual information of tag pairs via Google search results, 4) Applying natural language processing and machine learning techniques to extract semantic relations between tags. The experiment helped us to build a context sentence collection from the Google search results, which was then processed by natural language processing and machine learning algorithms. This new approach achieved a reasonably good rate of accuracy in assigning semantic relations to tag pairs. This paper also explores the implications of this approach for using social semantics to enrich subject metadata.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

Theme

Social tagging

0.085807584 = product of:
  0.17161517 = sum of:
    0.17161517 = sum of:
      0.13742718 = weight(_text_:tagging in 2754) [ClassicSimilarity], result of:
        0.13742718 = score(doc=2754,freq=4.0), product of:
          0.2979515 = queryWeight, product of:
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.05046712 = queryNorm
          0.4612401 = fieldWeight in 2754, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2754)
      0.03418799 = weight(_text_:22 in 2754) [ClassicSimilarity], result of:
        0.03418799 = score(doc=2754,freq=2.0), product of:
          0.17672725 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.05046712 = queryNorm
          0.19345059 = fieldWeight in 2754, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=2754)
  0.5 = coord(1/2)

Abstract

This article presents an exploratory study of Blobgects, an experimental interface for an online museum catalog that enables social tagging and blogging activity around a set of cultural heritage objects held by a preeminent museum of anthropology and archaeology. This study attempts to understand not just whether social tagging and commenting about these objects is useful but rather whose tags and voices matter in presenting different expert perspectives around digital museum objects. Based on an empirical comparison between two different user groups (Canadian Inuit high-school students and museum studies students in the United States), we found that merely adding the ability to tag and comment to the museum's catalog does not sufficiently allow users to learn about or engage with the objects represented by catalog entries. Rather, the specialist language of the catalog provides too little contextualization for users to enter into the sort of dialog that proponents of Web 2.0 technologies promise. Overall, we propose a more nuanced application of Web 2.0 technologies within museums - one which provides a contextual basis that gives users a starting point for engagement and permits users to make sense of objects in relation to their own needs, uses, and understandings.

Date

22. 3.2009 18:52:32

0.085807584 = product of:
  0.17161517 = sum of:
    0.17161517 = sum of:
      0.13742718 = weight(_text_:tagging in 1434) [ClassicSimilarity], result of:
        0.13742718 = score(doc=1434,freq=4.0), product of:
          0.2979515 = queryWeight, product of:
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.05046712 = queryNorm
          0.4612401 = fieldWeight in 1434, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.0390625 = fieldNorm(doc=1434)
      0.03418799 = weight(_text_:22 in 1434) [ClassicSimilarity], result of:
        0.03418799 = score(doc=1434,freq=2.0), product of:
          0.17672725 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.05046712 = queryNorm
          0.19345059 = fieldWeight in 1434, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0390625 = fieldNorm(doc=1434)
  0.5 = coord(1/2)

Abstract

Knowledge organization of large-scale content on the Web requires substantial amounts of semantic metadata that is expensive to generate manually. Recent developments in Web technologies have enabled any user to tag documents and other forms of content thereby generating metadata that could help organize knowledge. However, merely adding one or more tags to a document is highly inadequate to capture the aboutness of the document and thereby to support powerful semantic functions such as automatic classification, question answering or true semantic search and retrieval. This is true even when the tags used are labels from a well-designed classification system such as a thesaurus or taxonomy. There is a strong need to develop a semantic tagging mechanism with sufficient expressive power to capture the aboutness of each part of a document or dataset or multimedia content in order to enable applications that can benefit from knowledge organization on the Web. This article proposes a highly expressive mechanism of using ontology snippets as semantic tags that map portions of a document or a part of a dataset or a segment of a multimedia content to concepts and relations in an ontology of the domain(s) of interest.

Source

Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik

0.08415662 = product of:
  0.16831324 = sum of:
    0.16831324 = product of:
      0.33662647 = sum of:
        0.33662647 = weight(_text_:tagging in 764) [ClassicSimilarity], result of:
          0.33662647 = score(doc=764,freq=24.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.129803 = fieldWeight in 764, product of:
              4.8989797 = tf(freq=24.0), with freq of:
                24.0 = termFreq=24.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0390625 = fieldNorm(doc=764)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose - The purpose of the paper is to provide an overview of the collaborative tagging phenomenon and explore some of the reasons for its emergence. Design/methodology/approach - The paper reviews the related literature and discusses some of the problems associated with, and the potential of, collaborative tagging approaches for knowledge organisation and general resource discovery. A definition of controlled vocabularies is proposed and used to assess the efficacy of collaborative tagging. An exposition of the collaborative tagging model is provided and a review of the major contributions to the tagging literature is presented. Findings - There are numerous difficulties with collaborative tagging systems (e.g. low precision, lack of collocation, etc.) that originate from the absence of properties that characterise controlled vocabularies. However, such systems can not be dismissed. Librarians and information professionals have lessons to learn from the interactive and social aspects exemplified by collaborative tagging systems, as well as their success in engaging users with information management. The future co-existence of controlled vocabularies and collaborative tagging is predicted, with each appropriate for use within distinct information contexts: formal and informal. Research limitations/implications - Librarians and information professional researchers should be playing a leading role in research aimed at assessing the efficacy of collaborative tagging in relation to information storage, organisation, and retrieval, and to influence the future development of collaborative tagging systems. Practical implications - The paper indicates clear areas where digital libraries and repositories could innovate in order to better engage users with information. Originality/value - At time of writing there were no literature reviews summarising the main contributions to the collaborative tagging research or debate.

0.0833108 = product of:
  0.1666216 = sum of:
    0.1666216 = product of:
      0.3332432 = sum of:
        0.3332432 = weight(_text_:tagging in 2887) [ClassicSimilarity], result of:
          0.3332432 = score(doc=2887,freq=12.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.1184478 = fieldWeight in 2887, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2887)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

"Social Tagging" bezeichnet das gemeinsame Verwalten und Verschlagworten von Ressourcen und wird vor allem durch Dienste wie del.icio.us oder bibsonomy immer beliebter. Auch in Blogs wird mittlerweile getaggt. Der folgende Beitrag soll die Frage klären: Können Prozesse wie "wisdom of the crowd" und die Folksonomy mit strukturiert und hierarchisch arbeitenden Hochschulen in Verbindung gebracht werden? Obwohl Tagging im Kern verschiedene Dienste und Aufgaben an Hochschulen betrifft, bleibt die Frage bislang unbeantwortet, ob und wie dies an Hochschulen, vor allem im Prozess des Lehrens und Lernens integriert und nutzbar gemacht werden kann.

Footnote

Beitrag der Tagung "Social Tagging in der Wissensorganisation" am 21.-22.02.2008 am Institut für Wissensmedien (IWM) in Tübingen.

Source

Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a

Theme

Social tagging

0.0833108 = product of:
  0.1666216 = sum of:
    0.1666216 = product of:
      0.3332432 = sum of:
        0.3332432 = weight(_text_:tagging in 2888) [ClassicSimilarity], result of:
          0.3332432 = score(doc=2888,freq=12.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.1184478 = fieldWeight in 2888, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2888)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Der effiziente Zugang zu Informationen und Wissen spielt in allen Bereichen unserer heutigen Informationsgesellschaft eine Schlüsselrolle. Aufgrund der immer stärker zunehmenden digitalen Informationsflut ist es schwieriger denn je, aus all den zur Verfügung stehenden Ressourcen gerade die interessanten und benötigten Quellen herauszufiltern. Aus diesem Grund gehört eine Suchfunktion zur Grund( raussetzung von Informationssystemen verschiedenster Art. Dieser Artikel he schreibt die Einbettung von Social Tagging in kooperative Informationssysteme und zeigt verschiedene Synergieeffekte auf, die bei der Verzahnung einer klassi schen Suche im Zusammenspiel mit Tagging entstehen.

Footnote

Beitrag der Tagung "Social Tagging in der Wissensorganisation" am 21.-22.02.2008 am Institut für Wissensmedien (IWM) in Tübingen.

Source

Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a

Theme

Social tagging

0.082456306 = product of:
  0.16491261 = sum of:
    0.16491261 = product of:
      0.32982522 = sum of:
        0.32982522 = weight(_text_:tagging in 1730) [ClassicSimilarity], result of:
          0.32982522 = score(doc=1730,freq=16.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.1069763 = fieldWeight in 1730, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.046875 = fieldNorm(doc=1730)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

This paper presents a methodological discussion of a study of tagging quality in subject indexing. The data analysis in the study was divided into 3 phases: analysis of indexing consistency, analysis of tagging effectiveness, and analysis of the semantic values of tags. To analyze indexing consistency, this study employed the vector space model-based indexing consistency measures. An analysis of tagging effectiveness with tagging exhaustivity and tag specificity was conducted to ameliorate the drawbacks of consistency analysis based on only the quantitative measures of vocabulary matching. To further investigate the semantic values of tags at various levels of specificity, a latent semantic analysis (LSA) was conducted. To test statistical significance for the relation between tag specificity and semantic quality, correlation analysis was conducted. This research demonstrates the potential of tags for web document indexing with a complete assessment of tagging quality and provides a basis for further study of the strengths and limitations of tagging.

Theme

Social tagging

0.080573834 = product of:
  0.16114767 = sum of:
    0.16114767 = product of:
      0.32229534 = sum of:
        0.32229534 = weight(_text_:tagging in 3828) [ClassicSimilarity], result of:
          0.32229534 = score(doc=3828,freq=22.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.081704 = fieldWeight in 3828, product of:
              4.690416 = tf(freq=22.0), with freq of:
                22.0 = termFreq=22.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3828)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The purpose of this study is to understand users' motivations and intentions in the use of institutional collections on social tagging sites. Previous social tagging studies have collected social tagging data and analyzed how tagging functions as a tool to organize and retrieve information. Many studies focused on the patterns of tagging rather than the users' perspectives. To provide a more comprehensive picture of users' social tagging activities in institutional collections, and how this compares to social tagging in a more personal context, we collected data from social tagging users by surveying 7,563 participants in the Library of Congress's Flickr Collection. We asked users to describe their motivations for activities within the LC Flickr Collection in their own words using open-ended questions. As a result, we identified 11 motivations using a bottom-up, open-coding approach: affective reactions, opinion on photo, interest in subject, contribution to description, knowledge sharing, improving findability, social network, appreciation, personal use, and personal relationship. Our study revealed that affective or emotional reactions play a critical role in the use of social tagging of institutional collections by comparing our findings to existing frameworks for tagging motivations. We also examined the relationships between participants' occupations and our 11 motivations.

Theme

Social tagging

0.0788182 = product of:
  0.1576364 = sum of:
    0.1576364 = sum of:
      0.11661082 = weight(_text_:tagging in 2109) [ClassicSimilarity], result of:
        0.11661082 = score(doc=2109,freq=2.0), product of:
          0.2979515 = queryWeight, product of:
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.05046712 = queryNorm
          0.39137518 = fieldWeight in 2109, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.046875 = fieldNorm(doc=2109)
      0.041025586 = weight(_text_:22 in 2109) [ClassicSimilarity], result of:
        0.041025586 = score(doc=2109,freq=2.0), product of:
          0.17672725 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.05046712 = queryNorm
          0.23214069 = fieldWeight in 2109, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046875 = fieldNorm(doc=2109)
  0.5 = coord(1/2)

Date

1. 8.2008 12:39:22

0.0788182 = product of:
  0.1576364 = sum of:
    0.1576364 = sum of:
      0.11661082 = weight(_text_:tagging in 3387) [ClassicSimilarity], result of:
        0.11661082 = score(doc=3387,freq=2.0), product of:
          0.2979515 = queryWeight, product of:
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.05046712 = queryNorm
          0.39137518 = fieldWeight in 3387, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.046875 = fieldNorm(doc=3387)
      0.041025586 = weight(_text_:22 in 3387) [ClassicSimilarity], result of:
        0.041025586 = score(doc=3387,freq=2.0), product of:
          0.17672725 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.05046712 = queryNorm
          0.23214069 = fieldWeight in 3387, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046875 = fieldNorm(doc=3387)
  0.5 = coord(1/2)

Date

1. 8.2010 12:35:22

Theme

Social tagging

0.0788182 = product of:
  0.1576364 = sum of:
    0.1576364 = sum of:
      0.11661082 = weight(_text_:tagging in 3601) [ClassicSimilarity], result of:
        0.11661082 = score(doc=3601,freq=2.0), product of:
          0.2979515 = queryWeight, product of:
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.05046712 = queryNorm
          0.39137518 = fieldWeight in 3601, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.046875 = fieldNorm(doc=3601)
      0.041025586 = weight(_text_:22 in 3601) [ClassicSimilarity], result of:
        0.041025586 = score(doc=3601,freq=2.0), product of:
          0.17672725 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.05046712 = queryNorm
          0.23214069 = fieldWeight in 3601, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046875 = fieldNorm(doc=3601)
  0.5 = coord(1/2)

Date

10. 9.2000 17:38:22

Theme

Social tagging

0.0788182 = product of:
  0.1576364 = sum of:
    0.1576364 = sum of:
      0.11661082 = weight(_text_:tagging in 3602) [ClassicSimilarity], result of:
        0.11661082 = score(doc=3602,freq=2.0), product of:
          0.2979515 = queryWeight, product of:
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.05046712 = queryNorm
          0.39137518 = fieldWeight in 3602, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.046875 = fieldNorm(doc=3602)
      0.041025586 = weight(_text_:22 in 3602) [ClassicSimilarity], result of:
        0.041025586 = score(doc=3602,freq=2.0), product of:
          0.17672725 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.05046712 = queryNorm
          0.23214069 = fieldWeight in 3602, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046875 = fieldNorm(doc=3602)
  0.5 = coord(1/2)

Date

10. 9.2000 17:38:22

Theme

Social tagging

0.0788182 = product of:
  0.1576364 = sum of:
    0.1576364 = sum of:
      0.11661082 = weight(_text_:tagging in 2595) [ClassicSimilarity], result of:
        0.11661082 = score(doc=2595,freq=2.0), product of:
          0.2979515 = queryWeight, product of:
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.05046712 = queryNorm
          0.39137518 = fieldWeight in 2595, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.046875 = fieldNorm(doc=2595)
      0.041025586 = weight(_text_:22 in 2595) [ClassicSimilarity], result of:
        0.041025586 = score(doc=2595,freq=2.0), product of:
          0.17672725 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.05046712 = queryNorm
          0.23214069 = fieldWeight in 2595, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046875 = fieldNorm(doc=2595)
  0.5 = coord(1/2)

Abstract

Academic libraries have moved toward providing social networking features, such as tagging, in their library catalogs. To explore whether user tags can enhance access to individual literary works, the author obtained a sample of individual works of English and American literature from the twentieth and twenty-first centuries from a large academic library catalog and searched them in LibraryThing. The author compared match rates, the availability of subject headings and tags across various literary forms, and the terminology used in tags versus controlled-vocabulary headings on a subset of records. In addition, she evaluated the usefulness of available LibraryThing tags for the library catalog records that lacked subject headings. Options for utilizing the subject terms available in sources outside the local catalog also are discussed.

Date

10. 9.2000 17:38:22

0.0788182 = product of:
  0.1576364 = sum of:
    0.1576364 = sum of:
      0.11661082 = weight(_text_:tagging in 941) [ClassicSimilarity], result of:
        0.11661082 = score(doc=941,freq=2.0), product of:
          0.2979515 = queryWeight, product of:
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.05046712 = queryNorm
          0.39137518 = fieldWeight in 941, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            5.9038734 = idf(docFreq=327, maxDocs=44218)
            0.046875 = fieldNorm(doc=941)
      0.041025586 = weight(_text_:22 in 941) [ClassicSimilarity], result of:
        0.041025586 = score(doc=941,freq=2.0), product of:
          0.17672725 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.05046712 = queryNorm
          0.23214069 = fieldWeight in 941, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.046875 = fieldNorm(doc=941)
  0.5 = coord(1/2)

Date

22. 3.2023 12:00:14

0.07713082 = product of:
  0.15426163 = sum of:
    0.15426163 = product of:
      0.30852327 = sum of:
        0.30852327 = weight(_text_:tagging in 2271) [ClassicSimilarity], result of:
          0.30852327 = score(doc=2271,freq=14.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.0354816 = fieldWeight in 2271, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.046875 = fieldNorm(doc=2271)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Content

In investigating the use of social tagging for knowledge organization and sharing, this paper reports on two case studies. Each study examines how two disparate communities of practices utilize social tagging to disseminate information to other community members in the online environment. Through the use of these tags, community members may retrieve and view relevant Web sites and online videos. The first study looks at tagging within the Code4Lib community of practice. The second study examines the use of tagging on video sharing sites used by a community of French teenagers. Uses of social tagging to share information within these communities are analyzed and discussed, and recommendations for future study are provided.

Theme

Social tagging

0.07713082 = product of:
  0.15426163 = sum of:
    0.15426163 = product of:
      0.30852327 = sum of:
        0.30852327 = weight(_text_:tagging in 2883) [ClassicSimilarity], result of:
          0.30852327 = score(doc=2883,freq=14.0), product of:
            0.2979515 = queryWeight, product of:
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.05046712 = queryNorm
            1.0354816 = fieldWeight in 2883, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              5.9038734 = idf(docFreq=327, maxDocs=44218)
              0.046875 = fieldNorm(doc=2883)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

28 Prozent der amerikanischen Internetnutzer/innen haben es bereits getan: Das freie Verschlagworten von Inhalten aller Art per Social Tagging gehört zu den Anwendungen aus dem Kontext von Web 2.0, die sich zunehmender Beliebtheit erfreuen (Rainie, 2007). Während sich die bisherige Forschung überwiegend inhaltsanalytisch mit dem Phänomen befasst, kommen im vorliegenden Beitrag so genannte "Power User" zu Wort. Um zu einer fundierteren Interpretation der in den Inhaltsanalysen gewonnenen Erkenntnisse beizutragen, wurden Interviews mit Personen durchgeführt, die mehrere Tagging Systeme parallel einsetzen, sich auch mit den technischen Grundlagen auskennen und als "Early Adopter" bereits seit geraumer Zeit aktiv sind. Entsprechend leitet der Beitrag von einer Synopse der aktuellen Literatur in die beschriebene Studie über und schließt mit einem Ausblick auf zukünftige Forschungsvorhaben im Kontext von Social Tagging.

Footnote

Beitrag der Tagung "Social Tagging in der Wissensorganisation" am 21.-22.02.2008 am Institut für Wissensmedien (IWM) in Tübingen.

Source

Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a

Theme

Social tagging