-
Yi, K.: Harnessing collective intelligence in social tagging using Delicious (2012)
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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
-
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
-
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
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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
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Sun, A.; Bhowmick, S.S.; Nguyen, K.T.N.; Bai, G.: Tag-based social image retrieval : an empirical evaluation (2011)
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- Date
- 13. 2.2012 12:13:38
- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.12, S.2364-2381
-
Social tagging in a linked data environment. Edited by Diane Rasmussen Pennington and Louise F. Spiteri. London, UK: Facet Publishing, 2018. 240 pp. £74.95 (paperback). (ISBN 9781783303380) (2019)
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- Date
- 21. 1.2021 12:39:18
21. 1.2021 13:03:12
-
Raban, D.R.; Ronen, I.; Guy, I.: Acting or reacting? : Preferential attachment in a people-tagging system (2011)
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- Abstract
- Social technologies tend to attract research on social structure or interaction. In this paper we analyze the individual use of a social technology, specifically an enterprise people-tagging application. We focus on active participants of the system and distinguish between users who initiate activity and those who respond to activity. This distinction is situated within the preferential attachment theory in order to examine which type of participant contributes more to the process of tagging. We analyze the usage of the people-tagging application in a snapshot representing 3 years of activity, focusing on self-tagging compared to tagging by and of others. The main findings are: (1) People who tag themselves are the most productive contributors to the system. (2) Preferential attachment saturation is reached at 12-14 tags per user. (3) The nature of participation is more significant than the number of participants for system growth. The paper concludes with theoretical and practical implications.
-
Golbeck, J.; Koepfler, J.; Emmerling, B.: ¬An experimental study of social tagging behavior and image content (2011)
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- Date
- 27. 9.2011 12:45:42
-
Estellés Arolas, E.; González Ladrón-de-Guevar, F.: Uses of explicit and implicit tags in social bookmarking (2012)
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- Date
- 14. 2.2012 12:19:32
-
Konkova, E.; Göker, A.; Butterworth, R.; MacFarlane, A.: Social tagging: exploring the image, the tags, and the game (2014)
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- Date
- 3. 9.2014 13:12:34
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Bar-Ilan, J.; Zhitomirsky-Geffet, M.; Miller, Y.; Shoham, S.: ¬The effects of background information and social interaction on image tagging (2010)
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- Abstract
- In this article, we describe the results of an experiment designed to understand the effects of background information and social interaction on image tagging. The participants in the experiment were asked to tag 12 preselected images of Jewish cultural heritage. The users were partitioned into three groups: the first group saw only the images with no additional information whatsoever, the second group saw the images plus a short, descriptive title, and the third group saw the images, the titles, and the URL of the page in which the image appeared. In the first stage of the experiment, each user tagged the images without seeing the tags provided by the other users. In the second stage, the users saw the tags assigned by others and were encouraged to interact. Results show that after the social interaction phase, the tag sets converged and the popular tags became even more popular. Although in all cases the total number of assigned tags increased after the social interaction phase, the number of distinct tags decreased in most cases. When viewing the image only, in some cases the users were not able to correctly identify what they saw in some of the pictures, but they overcame the initial difficulties after interaction. We conclude from this experiment that social interaction may lead to convergence in tagging and that the wisdom of the crowds helps overcome the difficulties due to the lack of information.
-
Stvilia, B.; Jörgensen, C.: Member activities and quality of tags in a collection of historical photographs in Flickr (2010)
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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.12, S.2477-2489
-
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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- Date
- 12. 3.2001 11:34:20
-
Hsu, M.-H.; Chen, H.-H.: Efficient and effective prediction of social tags to enhance Web search (2011)
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- Date
- 27. 7.2011 19:34:12
-
Yoon, K.: Conceptual syntagmatic associations in user tagging (2012)
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- Date
- 11. 6.2012 14:12:10
-
Xu, C.; Ma, B.; Chen, X.; Ma, F.: Social tagging in the scholarly world (2013)
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- Date
- 25.10.2013 12:07:30
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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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- Date
- 19. 3.2016 12:05:52
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Choi, N.; Joo, S.: Booklovers' world : an examination of factors affecting continued usage of social cataloging sites (2016)
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- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.12, S.3022-3035
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Naderi, H.; Rumpler, B.: PERCIRS: a system to combine personalized and collaborative information retrieval (2010)
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- Date
- 29. 8.2010 12:59:10
