Search (142 results, page 1 of 8)

  • × theme_ss:"Social tagging"
  1. Kruk, S.R.; Kruk, E.; Stankiewicz, K.: Evaluation of semantic and social technologies for digital libraries (2009) 0.04 
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    Date
    1. 8.2010 12:35:22
    Type
    a
  2. Yi, K.: Harnessing collective intelligence in social tagging using Delicious (2012) 0.04 
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    Abstract
    A new collaborative approach in information organization and sharing has recently arisen, known as collaborative tagging or social indexing. A key element of collaborative tagging is the concept of collective intelligence (CI), which is a shared intelligence among all participants. This research investigates the phenomenon of social tagging in the context of CI with the aim to serve as a stepping-stone towards the mining of truly valuable social tags for web resources. This study focuses on assessing and evaluating the degree of CI embedded in social tagging over time in terms of two-parameter values, number of participants, and top frequency ranking window. Five different metrics were adopted and utilized for assessing the similarity between ranking lists: overlapList, overlapRank, Footrule, Fagin's measure, and the Inverse Rank measure. The result of this study demonstrates that a substantial degree of CI is most likely to be achieved when somewhere between the first 200 and 400 people have participated in tagging, and that a target degree of CI can be projected by controlling the two factors along with the selection of a similarity metric. The study also tests some experimental conditions for detecting social tags with high CI degree. The results of this study can be applicable to the study of filtering social tags based on CI; filtered social tags may be utilized for the metadata creation of tagged resources and possibly for the retrieval of tagged resources.
    Date
    25.12.2012 15:22:37
    Type
    a
  3. Farkas, M.G.: Social software in libraries : building collaboration, communication, and community online (2007) 0.02 
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    Classification
    BBK (FH K)
    Content
    Inhalt: What is social software? -- Blogs -- Blogs in libraries : practical applications -- RSS -- Wikis -- Online communities -- Social networking -- Social bookmarking and collaborative filtering -- Tools for synchronous online reference -- The mobile revolution -- Podcasting -- Screencasting and vodcasting -- Gaming -- What will work @ your library -- Keeping up : a primer -- Future trends in social software.
    GHBS
    BBK (FH K)
  4. Regulski, K.: Aufwand und Nutzen beim Einsatz von Social-Bookmarking-Services als Nachweisinstrument für wissenschaftliche Forschungsartikel am Beispiel von BibSonomy (2007) 0.02 
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    Type
    a
  5. Müller-Prove, M.: Modell und Anwendungsperspektive des Social Tagging (2008) 0.02 
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    Pages
    S.15-22
    Type
    a
  6. Hidderley, R.; Rafferty, P.: Flickr and democratic indexing : disciplining desire lines (2006) 0.02 
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    Abstract
    In this paper, we consider three models of subject indexing, and compare and contrast two indexing approaches, the theoretically based democratic indexing project, and Flickr, a working system for describing photographs. We argue that, despite Shirky's (2005) claim of philosophical paradigm shifting for social tagging, there is a residing doubt amongst information professionals that self-organising systems can work without there being some element of control and some form of 'representative authority'.
    Source
    Knowledge organization for a global learning society: Proceedings of the 9th International ISKO Conference, 4-7 July 2006, Vienna, Austria. Hrsg.: G. Budin, C. Swertz u. K. Mitgutsch
    Type
    a
  7. Golub, K.; Moon, J.; Nielsen, M.L.; Tudhope, D.: EnTag: Enhanced Tagging for Discovery (2008) 0.02 
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    Abstract
    Purpose: Investigate the combination of controlled and folksonomy approaches to support resource discovery in repositories and digital collections. Aim: Investigate whether use of an established controlled vocabulary can help improve social tagging for better resource discovery. Objectives: (1) Investigate indexing aspects when using only social tagging versus when using social tagging with suggestions from a controlled vocabulary; (2) Investigate above in two different contexts: tagging by readers and tagging by authors; (3) Investigate influence of only social tagging versus social tagging with a controlled vocabulary on retrieval. - Vgl.: http://www.ukoln.ac.uk/projects/enhanced-tagging/.
  8. Catarino, M.E.; Baptista, A.A.: Relating folksonomies with Dublin Core (2008) 0.02 
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    Abstract
    Folksonomy is the result of describing Web resources with tags created by Web users. Although it has become a popular application for the description of resources, in general terms Folksonomies are not being conveniently integrated in metadata. However, if the appropriate metadata elements are identified, then further work may be conducted to automatically assign tags to these elements (RDF properties) and use them in Semantic Web applications. This article presents research carried out to continue the project Kinds of Tags, which intends to identify elements required for metadata originating from folksonomies and to propose an application profile for DC Social Tagging. The work provides information that may be used by software applications to assign tags to metadata elements and, therefore, means for tags to be conveniently gathered by metadata interoperability tools. Despite the unquestionably high value of DC and the significance of the already existing properties in DC Terms, the pilot study show revealed a significant number of tags for which no corresponding properties yet existed. A need for new properties, such as Action, Depth, Rate, and Utility was determined. Those potential new properties will have to be validated in a later stage by the DC Social Tagging Community.
    Pages
    S.14-22
    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
    Type
    a
  9. Harrer, A.; Lohmann, S.: Potenziale von Tagging als partizipative Methode für Lehrportale und E-Learning-Kurse (2008) 0.02 
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    Date
    21. 6.2009 12:22:44
    Type
    a
  10. Tschetschonig, K.; Ladengruber, R.; Hampel, T.; Schulte, J.: Kollaborative Tagging-Systeme im Electronic Commerce (2008) 0.02 
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    a
  11. Rolla, P.J.: User tags versus Subject headings : can user-supplied data improve subject access to library collections? (2009) 0.01 
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    Abstract
    Some members of the library community, including the Library of Congress Working Group on the Future of Bibliographic Control, have suggested that libraries should open up their catalogs to allow users to add descriptive tags to the bibliographic data in catalog records. The web site LibraryThing currently permits its members to add such user tags to its records for books and therefore provides a useful resource to contrast with library bibliographic records. A comparison between the LibraryThing tags for a group of books and the library-supplied subject headings for the same books shows that users and catalogers approach these descriptors very differently. Because of these differences, user tags can enhance subject access to library materials, but they cannot entirely replace controlled vocabularies such as the Library of Congress subject headings.
    Date
    10. 9.2000 17:38:22
    Type
    a
  12. Strader, C.R.: Author-assigned keywords versus Library of Congress Subject Headings : implications for the cataloging of electronic theses and dissertations (2009) 0.01 
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    Abstract
    This study is an examination of the overlap between author-assigned keywords and cataloger-assigned Library of Congress Subject Headings (LCSH) for a set of electronic theses and dissertations in Ohio State University's online catalog. The project is intended to contribute to the literature on the issue of keywords versus controlled vocabularies in the use of online catalogs and databases. Findings support previous studies' conclusions that both keywords and controlled vocabularies complement one another. Further, even in the presence of bibliographic record enhancements, such as abstracts or summaries, keywords and subject headings provided a significant number of unique terms that could affect the success of keyword searches. Implications for the maintenance of controlled vocabularies such as LCSH also are discussed in light of the patterns of matches and nonmatches found between the keywords and their corresponding subject headings.
    Date
    10. 9.2000 17:38:22
    Type
    a
  13. Sun, A.; Bhowmick, S.S.; Nguyen, K.T.N.; Bai, G.: Tag-based social image retrieval : an empirical evaluation (2011) 0.01 
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    Abstract
    Tags associated with social images are valuable information source for superior image search and retrieval experiences. Although various heuristics are valuable to boost tag-based search for images, there is a lack of general framework to study the impact of these heuristics. Specifically, the task of ranking images matching a given tag query based on their associated tags in descending order of relevance has not been well studied. In this article, we take the first step to propose a generic, flexible, and extensible framework for this task and exploit it for a systematic and comprehensive empirical evaluation of various methods for ranking images. To this end, we identified five orthogonal dimensions to quantify the matching score between a tagged image and a tag query. These five dimensions are: (i) tag relatedness to measure the degree of effectiveness of a tag describing the tagged image; (ii) tag discrimination to quantify the degree of discrimination of a tag with respect to the entire tagged image collection; (iii) tag length normalization analogous to document length normalization in web search; (iv) tag-query matching model for the matching score computation between an image tag and a query tag; and (v) query model for tag query rewriting. For each dimension, we identify a few implementations and evaluate their impact on NUS-WIDE dataset, the largest human-annotated dataset consisting of more than 269K tagged images from Flickr. We evaluated 81 single-tag queries and 443 multi-tag queries over 288 search methods and systematically compare their performances using standard metrics including Precision at top-K, Mean Average Precision (MAP), Recall, and Normalized Discounted Cumulative Gain (NDCG).
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    a
  14. Niemann, C.: Tag-Science : Ein Analysemodell zur Nutzbarkeit von Tagging-Daten (2011) 0.01 
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    Source
    ¬Die Kraft der digitalen Unordnung: 32. Arbeits- und Fortbildungstagung der ASpB e. V., Sektion 5 im Deutschen Bibliotheksverband, 22.-25. September 2009 in der Universität Karlsruhe. Hrsg: Jadwiga Warmbrunn u.a
    Type
    a
  15. Yi, K.: ¬A semantic similarity approach to predicting Library of Congress subject headings for social tags (2010) 0.01 
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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.
    Type
    a
  16. Qin, C.; Liu, Y.; Mou, J.; Chen, J.: User adoption of a hybrid social tagging approach in an online knowledge community (2019) 0.01 
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    Abstract
    Purpose Online knowledge communities make great contributions to global knowledge sharing and innovation. Resource tagging approaches have been widely adopted in such communities to describe, annotate and organize knowledge resources mainly through users' participation. However, it is unclear what causes the adoption of a particular resource tagging approach. The purpose of this paper is to identify factors that drive users to use a hybrid social tagging approach. Design/methodology/approach Technology acceptance model and social cognitive theory are adopted to support an integrated model proposed in this paper. Zhihu, one of the most popular online knowledge communities in China, is taken as the survey context. A survey was conducted with a questionnaire and collected data were analyzed through structural equation model. Findings A new hybrid social resource tagging approach was refined and described. The empirical results revealed that self-efficacy, perceived usefulness (PU) and perceived ease of use exert positive effect on users' attitude. Moreover, social influence, PU and attitude impact significantly on users' intention to use a hybrid social resource tagging approach. Originality/value Theoretically, this study enriches the type of resource tagging approaches and recognizes factors influencing user adoption to use it. Regarding the practical parts, the results provide online information system providers and designers with referential strategies to improve the performance of the current tagging approaches and promote them.
    Date
    20. 1.2015 18:30:22
    Type
    a
  17. Munk, T.B.; Moerk, K.: Folksonomies, tagging communities, and tagging strategies : an empirical study (2007) 0.01 
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    Abstract
    The subject of this article is folksonomies on the Internet. One of the largest folksonomies on the Internet in terms of number of users and tagged websites is the computer program del.icio.us, where more than 100,000 people have tagged the websites that they and others find using their own keywords. How this is done in practice and the patterns to be found are the focus of this article. The empirical basis is the collection of 76,601 different keywords with a total frequency of 178,215 from 500 randomly chosen taggers on del.icio.us at the end of 2005. The keywords collected were then analyzed quantitatively statistically by uncovering their frequency and percentage distribution and through a statistical correspondence analysis in order to uncover possible patterns in the users' tags. Subsequently, a qualitative textual analysis of the tags was made in order to find out by analysis which tagging strategies are represented in the data material. This led to four conclusions. 1) the distribution of keywords follows classic power law; 2) distinct tagging communities are identifiable; 3) the most frequently used tags are situated on a general-specific axis; and 4) nine distinct tagging strategies are observed. These four conclusions are put into perspective collectively in respect of a number of more general and theoretical considerations concerning folksonomies and the classification systems of the future.
    Type
    a
  18. Chopin, K.: Finding communities : alternative viewpoints through weblogs and tagging (2008) 0.01 
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    Abstract
    Purpose - This paper aims to discuss and test the claim that user-based tagging allows for access to a wider variety of viewpoints than is found using other forms of online searching. Design/methodology/approach - A general overview of the nature of weblogs and user-based tagging is given, along with other relevant concepts. A case is then analyzed where viewpoints towards a specific issue are searched for using both tag searching (Technorati) and general search engine searching (Google and Google Blog Search). Findings - The claim to greater accessibility through user-based tagging is not overtly supported with these experiments. Further results for both general and tag-specific searching goes against some common assumptions about the types of content found on weblogs as opposed to more general web sites. Research limitations/implications - User-based tagging is still not widespread enough to give conclusive data for analysis. As this changes, further research in this area, using a variety of search subjects, is warranted. Originality/value - Although proponents of user-based tagging attribute many qualities to the practice, these qualities have not been properly documented or demonstrated. This paper partially rectifies this gap by testing one of the claims made, that of accessibility to alternate views, thus adding to the discussion on tagging for both researchers and other interested parties.
    Type
    a
  19. 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) 0.01 
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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.
    Type
    a
  20. Yoon, K.: Conceptual syntagmatic associations in user tagging (2012) 0.01 
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    Abstract
    This study aimed to integrate the linguistic theory of syntagmatic relations and the concept of topic and comment into an empirical analysis of user tagging. User tags on documents in a social bookmarking site reflect a user's views of an information object, which can augment the content description and provide more effective representation of information. The study presents a study of tag analysis to uncover semantic relations among tag terms implicit in user tagging. The objective was to identify the syntagmatic semantic cores of topic and comment in user tags evidenced by the meaning attached to the information object by users. The study focused on syntagmatic relations, which were based on the way in which terms were used within the information content among users. Analysis of descriptive tag terms found three primary categories of concepts: content-topic, content-comment, and context of use. The relations among terms within a group and between the content-topic and content-comment groups were determined by inferring user meaning from the user notes and from the context of the source text. Intergroup relations showed syntagmatic associations between the topic and comment, whereas intragroup relations were more general but were limited in the document context. The findings are discussed with regard to the semantics of concepts and relations in user tagging. An implication of syntagmatic relations to information search suggests that concepts can be combined by a specific association in the context of the actual use of terms.
    Type
    a

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