-
Niemann, C.: Tag-Science : Ein Analysemodell zur Nutzbarkeit von Tagging-Daten (2011)
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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
-
Qin, C.; Liu, Y.; Mou, J.; Chen, J.: User adoption of a hybrid social tagging approach in an online knowledge community (2019)
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- Date
- 20. 1.2015 18:30:22
-
Huang, S.-L.; Lin, S.-C.; Chan, Y.-C.: Investigating effectiveness and user acceptance of semantic social tagging for knowledge sharing (2012)
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Xu, C.; Ma, B.; Chen, X.; Ma, F.: Social tagging in the scholarly world (2013)
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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.
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Watters, C.; Nizam, N.: Knowledge organization on the Web : the emergent role of social classification (2012)
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-
Yi, K.: Harnessing collective intelligence in social tagging using Delicious (2012)
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- Date
- 25.12.2012 15:22:37
-
Choi, Y.; Syn, S.Y.: Characteristics of tagging behavior in digitized humanities online collections (2016)
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- Date
- 21. 4.2016 11:23:22
-
Nov, O.; Naaman, M.; Ye, C.: Analysis of participation in an online photo-sharing community : a multidimensional perspective (2010)
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-
Huang, C.; Fu, T.; Chen, H.: Text-based video content classification for online video-sharing sites (2010)
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-
Stvilia, B.; Jörgensen, C.: Member activities and quality of tags in a collection of historical photographs in Flickr (2010)
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-
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)
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-
Niemann, C.: Intelligenz im Chaos : erste Schritte zur Analyse des Kreativen Potenzials eines Tagging-Systems (2010)
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-
Li, D.; Ding, Y.; Sugimoto, C.; He, B.; Tang, J.; Yan, E.; Lin, N.; Qin, Z.; Dong, T.: Modeling topic and community structure in social tagging : the TTR-LDA-Community model (2011)
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-
Lin, N.; Li, D.; Ding, Y.; He, B.; Qin, Z.; Tang, J.; Li, J.; Dong, T.: ¬The dynamic features of Delicious, Flickr, and YouTube (2012)
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- Abstract
- This article investigates the dynamic features of social tagging vocabularies in Delicious, Flickr, and YouTube from 2003 to 2008. Three algorithms are designed to study the macro- and micro-tag growth as well as the dynamics of taggers' activities, respectively. Moreover, we propose a Tagger Tag Resource Latent Dirichlet Allocation (TTR-LDA) model to explore the evolution of topics emerging from those social vocabularies. Our results show that (a) at the macro level, tag growth in all the three tagging systems obeys power law distribution with exponents lower than 1; at the micro level, the tag growth of popular resources in all three tagging systems follows a similar power law distribution; (b) the exponents of tag growth vary in different evolving stages of resources; (c) the growth of number of taggers associated with different popular resources presents a feature of convergence over time; (d) the active level of taggers has a positive correlation with the macro-tag growth of different tagging systems; and (e) some topics evolve into several subtopics over time while others experience relatively stable stages in which their contents do not change much, and certain groups of taggers continue their interests in them.
-
Choi, Y.: ¬A Practical application of FRBR for organizing information in digital environments (2012)
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- Content
- This paper is derived from the author's doctoral dissertation "Usefulness of Social Tagging in Organizing and Providing Access An Analysis of Indexing Consistency and Quality." The author is deeply grateful to her dissertation committee-Dr. Linda C. Smith chairperson, Drs. Allen Renear, Miles Efron and John Unsworth. Vgl.: http://www.ergon-verlag.de/isko_ko/downloads/ko_39_2012_4_a.pdf.
-
Huang, H.; Jörgensen, C.: Characterizing user tagging and Co-occurring metadata in general and specialized metadata collections (2013)
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-
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)
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Xu, C.; Zhang, Q.: ¬The dominant factor of social tags for users' decision behavior on e-commerce websites : color or text (2019)
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-
Hänger, C.; Krätzsch, C.; Niemann, C.: Was vom Tagging übrig blieb : Erkenntnisse und Einsichten aus zwei Jahren Projektarbeit (2011)
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