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  • × theme_ss:"Social tagging"
  1. Niemann, C.: Tag-Science : Ein Analysemodell zur Nutzbarkeit von Tagging-Daten (2011) 0.02 
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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
  2. Yi, K.: Harnessing collective intelligence in social tagging using Delicious (2012) 0.02 
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    Date
    25.12.2012 15:22:37
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.12, S.2488-2502
  3. Choi, Y.; Syn, S.Y.: Characteristics of tagging behavior in digitized humanities online collections (2016) 0.02 
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    Date
    21. 4.2016 11:23:22
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.5, S.1089-1104
  4. Bentley, C.M.; Labelle, P.R.: ¬A comparison of social tagging designs and user participation (2008) 0.02 
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    Abstract
    Social tagging empowers users to categorize content in a personally meaningful way while harnessing their potential to contribute to a collaborative construction of knowledge (Vander Wal, 2007). In addition, social tagging systems offer innovative filtering mechanisms that facilitate resource discovery and browsing (Mathes, 2004). As a result, social tags may support online communication, informal or intended learning as well as the development of online communities. The purpose of this mixed methods study is to examine how undergraduate students participate in social tagging activities in order to learn about their motivations, behaviours and practices. A better understanding of their knowledge, habits and interactions with such systems will help practitioners and developers identify important factors when designing enhancements. In the first phase of the study, students enrolled at a Canadian university completed 103 questionnaires. Quantitative results focusing on general familiarity with social tagging, frequently used Web 2.0 sites, and the purpose for engaging in social tagging activities were compiled. Eight questionnaire respondents participated in follow-up semi-structured interviews that further explored tagging practices by situating questionnaire responses within concrete experiences using popular websites such as YouTube, Facebook, Del.icio.us, and Flickr. Preliminary results of this study echo findings found in the growing literature concerning social tagging from the fields of computer science (Sen et al., 2006) and information science (Golder & Huberman, 2006; Macgregor & McCulloch, 2006). Generally, two classes of social taggers emerge: those who focus on tagging for individual purposes, and those who view tagging as a way to share or communicate meaning to others. Heavy del.icio.us users, for example, were often focused on simply organizing their own content, and seemed to be conscientiously maintaining their own personally relevant categorizations while, in many cases, placing little importance on the tags of others. Conversely, users tagging items primarily to share content preferred to use specific terms to optimize retrieval and discovery by others. Our findings should inform practitioners of how interaction design can be tailored for different tagging systems applications, and how these findings are positioned within the current debate surrounding social tagging among the resource discovery community. We also hope to direct future research in the field to place a greater importance on exploring the benefits of tagging as a socially-driven endeavour rather than uniquely as a means of managing information.
    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
  5. Hunter, J.: Collaborative semantic tagging and annotation systems (2009) 0.01 
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    Source
    Annual review of information science and technology. 43(2009), S.xxx-xxx
  6. Vander Wal, T.: Welcome to the Matrix! (2008) 0.01 
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    Abstract
    My keynote at the workshop "Social Tagging in Knowledge Organization" was a great opportunity to make and share new experiences. For the first time ever, I sat in my office at home and gave a live web video presentation to a conference audience elsewhere on the globe. At the same time, it was also an opportunity to premier my conceptual model "Matrix of Perception" to an interdisciplinary audience of researchers and practitioners with a variety of backgrounds - reaching from philosophy, psychology, pedagogy and computation to library science and economics. The interdisciplinary approach of the conference is also mirrored in the structure of this volume, with articles on the theoretical background, the empirical analysis and the potential applications of tagging, for instance in university libraries, e-learning, or e-commerce. As an introduction to the topic of "social tagging" I would like to draw your attention to some foundation concepts of the phenomenon I have racked my brain with for the last few month. One thing I have seen missing in recent research and system development is a focus on the variety of user perspectives in social tagging. Different people perceive tagging in complex variegated ways and use this form of knowledge organization for a variety of purposes. My analytical interest lies in understanding the personas and patterns in tagging systems and in being able to label their different perceptions. To come up with a concise picture of user expectations, needs and activities, I have broken down the perspectives on tagging into two different categories, namely "faces" and "depth". When put together, they form the "Matrix of Perception" - a nuanced view of stakeholders and their respective levels of participation.
    Date
    22. 6.2009 9:15:45
  7. Wolfram, D.; Olson, H.A.; Bloom, R.: Measuring consistency for multiple taggers using vector space modeling (2009) 0.01 
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    Abstract
    A longstanding area of study in indexing is the identification of factors affecting vocabulary usage and consistency. This topic has seen a recent resurgence with a focus on social tagging. Tagging data for scholarly articles made available by the social bookmarking Website CiteULike (www.citeulike.org) were used to test the use of inter-indexer/tagger consistency density values, based on a method developed by the authors by comparing calculations for highly tagged documents representing three subject areas (Science, Social Science, Social Software). The analysis revealed that the developed method is viable for a large dataset. The findings also indicated that there were no significant differences in tagging consistency among the three topic areas, demonstrating that vocabulary usage in a relatively new subject area like social software is no more inconsistent than the more established subject areas investigated. The implications of the method used and the findings are discussed.
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.10, S.1995-2003
  8. Wang, J.; Clements, M.; Yang, J.; Vries, A.P. de; Reinders, M.J.T.: Personalization of tagging systems (2010) 0.01 
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    Abstract
    Social media systems have encouraged end user participation in the Internet, for the purpose of storing and distributing Internet content, sharing opinions and maintaining relationships. Collaborative tagging allows users to annotate the resulting user-generated content, and enables effective retrieval of otherwise uncategorised data. However, compared to professional web content production, collaborative tagging systems face the challenge that end-users assign tags in an uncontrolled manner, resulting in unsystematic and inconsistent metadata. This paper introduces a framework for the personalization of social media systems. We pinpoint three tasks that would benefit from personalization: collaborative tagging, collaborative browsing and collaborative search. We propose a ranking model for each task that integrates the individual user's tagging history in the recommendation of tags and content, to align its suggestions to the individual user preferences. We demonstrate on two real data sets that for all three tasks, the personalized ranking should take into account both the user's own preference and the opinion of others.
  9. Xu, C.; Ma, B.; Chen, X.; Ma, F.: Social tagging in the scholarly world (2013) 0.01 
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    Abstract
    The number of research studies on social tagging has increased rapidly in the past years, but few of them highlight the characteristics and research trends in social tagging. A set of 862 academic documents relating to social tagging and published from 2005 to 2011 was thus examined using bibliometric analysis as well as the social network analysis technique. The results show that social tagging, as a research area, develops rapidly and attracts an increasing number of new entrants. There are no key authors, publication sources, or research groups that dominate the research domain of social tagging. Research on social tagging appears to focus mainly on the following three aspects: (a) components and functions of social tagging (e.g., tags, tagging objects, and tagging network), (b) taggers' behaviors and interface design, and (c) tags' organization and usage in social tagging. The trend suggest that more researchers turn to the latter two integrated with human computer interface and information retrieval, although the first aspect is the fundamental one in social tagging. Also, more studies relating to social tagging pay attention to multimedia tagging objects and not only text tagging. Previous research on social tagging was limited to a few subject domains such as information science and computer science. As an interdisciplinary research area, social tagging is anticipated to attract more researchers from different disciplines. More practical applications, especially in high-tech companies, is an encouraging research trend in social tagging.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.10, S.2045-2057
  10. Farkas, M.G.: Social software in libraries : building collaboration, communication, and community online (2007) 0.01 
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    LCSH
    Wikis (Computer science)
    Subject
    Wikis (Computer science)
  11. Shiri, A.: Trend analysis in social tagging : an LIS perspective (2007) 0.01 
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    Abstract
    The aim of the present study was to identify and categorize social tagging trends and developments as revealed by the analysis of library and information science scholarly and professional literature.
  12. Xu, C.; Zhang, Q.: ¬The dominant factor of social tags for users' decision behavior on e-commerce websites : color or text (2019) 0.01 
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    Footnote
    Beitrag in einem 'Special issue on neuro-information science'.
    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.9, S.942-953
  13. Müller-Prove, M.: Modell und Anwendungsperspektive des Social Tagging (2008) 0.01 
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    Pages
    S.15-22
  14. Catarino, M.E.; Baptista, A.A.: Relating folksonomies with Dublin Core (2008) 0.01 
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    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
  15. Trant, J.; Bearman, D.: Social terminology enhancement through vernacular engagement : exploring collaborative annotation to encourage interaction with museum collections (2005) 0.01 
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    Abstract
    From their earliest encounters with the Web, museums have seen an opportunity to move beyond uni-directional communication into an environment that engages their users and reflects a multiplicity of perspectives. Shedding the "Unassailable Voice" (Walsh 1997) in favor of many "Points of View" (Sledge 1995) has challenged traditional museum approaches to the creation and delivery of content. Novel approaches are required in order to develop and sustain user engagement (Durbin 2004). New models of exhibit creation that democratize the curatorial functions of object selection and interpretation offer one way of opening up the museum (Coldicutt and Streten 2005). Another is to use the museum as a forum and focus for community story-telling (Howard, Pratty et al. 2005). Unfortunately, museum collections remain relatively inaccessible even when 'made available' through searchable on-line databases. Museum documentation seldom satisfies the on-line access needs of the broad public, both because it is written using professional terminology and because it may not address what is important to - or remembered by - the museum visitor. For example, an exhibition now on-line at The Metropolitan Museum of Art acknowledges "Coco" Chanel only in the brief, textual introduction (The Metropolitan Museum of Art 2005a). All of the images of her delightful fashion designs are attributed to "Gabrielle Chanel" (The Metropolitan Museum of Art 2005a). Interfaces that organize collections along axes of time or place - such of that of the Timeline of Art History (The Metropolitan Museum of Art 2005e) - often fail to match users' world-views, despite the care that went into their structuring or their significant pedagogical utility. Critically, as professionals working with art museums we realize that when cataloguers and curators describe works of art, they usually do not include the "subject" of the image itself. Simply put, we rarely answer the question "What is it a picture of?" Unfortunately, visitors will often remember a work based on its visual characteristics, only to find that Web-based searches for any of the things they recall do not produce results.
  16. Harrer, A.; Lohmann, S.: Potenziale von Tagging als partizipative Methode für Lehrportale und E-Learning-Kurse (2008) 0.01 
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    Date
    21. 6.2009 12:22:44
  17. Ding, Y.; Jacob, E.K.; Zhang, Z.; Foo, S.; Yan, E.; George, N.L.; Guo, L.: Perspectives on social tagging (2009) 0.01 
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    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.12, S.2388-2401
  18. Ding, Y.; Jacob, E.K.; Fried, M.; Toma, I.; Yan, E.; Foo, S.; Milojevicacute, S.: Upper tag ontology for integrating social tagging data (2010) 0.01 
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    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.3, S.505-521
  19. Antin, J.; Earp, M.: With a little help from my friends : self-interested and prosocial behavior on MySpace Music (2010) 0.01 
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    Journal of the American Society for Information Science and Technology. 61(2010) no.5, S.952-963
  20. Raban, D.R.; Ronen, I.; Guy, I.: Acting or reacting? : Preferential attachment in a people-tagging system (2011) 0.01 
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