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Erschienen in:
Introduction to Social Information Access Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Tag-Based Navigation and Visualization

verfasst von : Dimitar Dimitrov, Denis Helic, Markus Strohmaier

Erschienen in: Social Information Access

Verlag: Springer International Publishing

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Abstract

Allowing users to organize content by tagging resources in webbased systems has led to the emergence of the so-called SocialWeb. Tags turned out to be helpful not only for giving recommendations and improving search in social tagging systems but also for enhancing information access by navigating. In this chapter, we will cover much of the pioneer research work that has studied tag-based navigation and visualization. After giving a short overview of the social tagging process and its specifics, we provide an extensive description of the typical user interfaces and visualization techniques characteristic for social tagging systems. As the efficiency of tag-based navigation depends on structuring tagging data, we also provide a review of the state of the art algorithms for tag clustering. Before we conclude, we demonstrate how tag-based navigation can be modeled and discuss the intrinsic navigability of social tagging systems from various theoretic perspectives.

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Vorheriges Kapitel Social Navigation
Nächstes Kapitel Social Search
Fußnoten
1
DMOZ has been closed as of Mar 17, 2017, and it is no longer available under https://​www.​dmoz.​org. The editors have set up a static mirror under http://​dmoztools.​net/​.
 
Literatur
1.
Adamic, L.A., Lukose, R.M., Puniyani, A.R., Huberman, B.A.: Search in power-law networks. Phys. Rev. E 64(4), 046135 (2001)CrossRef
2.
3.
Au Yeung, C., Gibbins, N., Shadbolt, N.: Contextualising tags in collaborative tagging systems. In: Proceedings of the 20th ACM Conference on Hypertext and Hypermedia, HT 2009, pp. 251–260. ACM, New York (2009)
4.
Bateman, S., Gutwin, C., Nacenta, M.: Seeing things in the clouds: the effect of visual features on tag cloud selections. In: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia, HT 2008, pp. 193–202. ACM, New York (2008)
5.
Begelman, G., Keller, P., Smadja, F.: Automated tag clustering: improving search and exploration in the tag space. In: Collaborative web tagging workshop at WWW 2006, vol. 50, Edinburgh, Scotland (2006)
6.
Benz, D., Hotho, A., Stumme, G., Sttzer, S.: Semantics made by you and me: self-emerging ontologies can capture the diversity of shared knowledge. In: Proceedings of the 2nd Web Science Conference, WebSci 2010 (2010)
7.
Bielenberg, K., Zacher, M.: Groups in social software: utilizing tagging to integrate individual contexts for social navigation (2006)
8.
Bogers, T.: Tag-based recommendation. In: Brusilovsky, P., He, D. (eds.) Social Information Access. LNCS, vol. 10100, pp. 441–479. Springer, Cham (2018)
9.
Borges, J., Levene, M.: Evaluating variable-length markov chain models for analysis of user web navigation sessions. IEEE Trans. Knowl. Data Eng. 19(4), 441–452 (2007)CrossRef
10.
11.
Brooks, C.H., Montanez, N.: Improved annotation of the blogosphere via autotagging and hierarchical clustering. In: Proceedings of the 15th International Conference on World Wide Web, WWW 2006, pp. 625–632. ACM, New York (2006)
12.
Candan, K.S., Di Caro, L., Sapino, M.L.: Creating tag hierarchies for effective navigation in social media. In: Proceedings of the 2008 ACM Workshop on Search in Social Media, SSM 2008, pp. 75–82. ACM, New York (2008)
13.
Cattuto, C., Schmitz, C., Baldassarri, A., Servedio, V.D., Loreto, V., Hotho, A., Grahl, M., Stumme, G.: Network properties of folksonomies. AI Commun. 20(4), 245–262 (2007)MathSciNet
14.
Chi, E.H., Mytkowicz, T.: Understanding navigability of social tagging systems. In: Proceedings of CHI, vol. 7 (2007)
15.
Chi, E.H., Mytkowicz, T.: Understanding the efficiency of social tagging systems using information theory. In: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia, HT 2008, pp. 81–88. ACM, New York (2008)
16.
Clauset, A., Moore, C., Newman, M.E.: Hierarchical structure and the prediction of missing links in networks. Nature 453(7191), 98–101 (2008)CrossRef
17.
Collins, C., Viegas, F.B., Wattenberg, M.: Parallel tag clouds to explore and analyze faceted text corpora. In: IEEE Symposium on Visual Analytics Science and Technology, VAST 2009, pp. 91–98. IEEE (2009)
18.
Daw, N.D., O’Doherty, J.P., Dayan, P., Seymour, B., Dolan, R.J.: Cortical substrates for exploratory decisions in humans. Nature 441(7095), 876–879 (2006)CrossRef
19.
Deshpande, M., Karypis, G.: Selective markov models for predicting web page accesses. ACM Trans. Internet Technol. (TOIT) 4(2), 163–184 (2004)CrossRef
20.
Dhillon, I.S., Fan, J., Guan, Y.: Efficient clustering of very large document collections. In: Grossman, R.L., Kamath, C., Kegelmeyer, P., Kumar, V., Namburu, R.R. (eds.) Data Mining for Scientific and Engineering Applications. MC, vol. 2, pp. 357–381. Springer, Boston, MA (2001). https://​doi.​org/​10.​1007/​978-1-4615-1733-7_​20CrossRef
21.
Di Caro, L., Candan, K.S., Sapino, M.L.: Using tagflake for condensing navigable tag hierarchies from tag clouds. In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008, pp. 1069–1072. ACM, New York (2008)
22.
Dubinko, M., Kumar, R., Magnani, J., Novak, J., Raghavan, P., Tomkins, A.: Visualizing tags over time. ACM Trans. Web 1(2), 7 (2007)CrossRef
23.
Eda, T., Uchiyama, T., Uchiyama, T., Yoshikawa, M.: Signaling emotion in tagclouds. In: Proceedings of the 18th International Conference on World Wide Web, WWW 2009, pp. 1199–1200. ACM, New York (2009)
24.
Fairthorne, R.A.: Content analysis, specification and control. Annu. Rev. Inf. Sci. Technol. 4, 73–109 (1969)
25.
Forgy, E.W.: Cluster analysis of multivariate data: efficiency versus interpretability of classifications. Biometrics 21, 768–769 (1965)
26.
27.
Fu, W.T., Pirolli, P.: SNIF-ACT: a cognitive model of user navigation on the world wide web. Hum.-Comput. Interact. 22(4), 355–412 (2007)
28.
Furnas, G.W., Fake, C., von Ahn, L., Schachter, J., Golder, S., Fox, K., Davis, M., Marlow, C., Naaman, M.: Why do tagging systems work? In: CHI 2006 Extended Abstracts on Human Factors in Computing Systems, CHI EA 2006, pp. 36–39. ACM, New York (2006)
29.
Furnas, G.W., Landauer, T.K., Gomez, L.M., Dumais, S.T.: The vocabulary problem in human-system communication. Commun. ACM 30(11), 964–971 (1987)CrossRef
30.
31.
Golder, S.A., Huberman, B.A.: Usage patterns of collaborative tagging systems. J. Inf. Sci. 32(2), 198–208 (2006)CrossRef
32.
Halvey, M.J., Keane, M.T.: An assessment of tag presentation techniques. In: Proceedings of the 16th International Conference on World Wide Web, WWW 2007, pp. 1313–1314. ACM, New York (2007)
33.
Hassan-Montero, Y., Herrero-Solana, V.: Improving tag-clouds as visual information retrieval interfaces. In: International Conference on Multidisciplinary Information Sciences and Technologies, InSciT 2006 (2006)
34.
Hearst, M.: Search User Interfaces. Cambridge University Press, Cambridge (2009)CrossRef
35.
Helic, D., Körner, C., Granitzer, M., Strohmaier, M., Trattner, C.: Navigational efficiency of broad vs. narrow folksonomies. In: Proceedings of the 23rd ACM Conference on Hypertext and Social Media, HT 2012, pp. 63–72. ACM, New York (2012)
36.
Helic, D., Strohmaier, M.: Building directories for social tagging systems. In: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, CIKM 2011, pp. 525–534. ACM, New York (2011)
37.
Helic, D., Strohmaier, M., Granitzer, M., Scherer, R.: Models of human navigation in information networks based on decentralized search. In: Proceedings of the 24th ACM Conference on Hypertext and Social Media, HT 2013, pp. 89–98. ACM, New York (2013). https://​doi.​org/​10.​1145/​2481492.​2481502
38.
Helic, D., Strohmaier, M., Trattner, C., Muhr, M., Lerman, K.: Pragmatic evaluation of folksonomies. In: Proceedings of the 20th International Conference on World Wide Web, WWW 2011, pp. 417–426. ACM, New York (2011)
39.
Helic, D., Trattner, C., Strohmaier, M., Andrews, K.: On the navigability of social tagging systems. In: 2010 IEEE Second International Conference on Social Computing (SocialCom), pp. 161–168. IEEE (2010)
40.
Helic, D., Trattner, C., Strohmaier, M., Andrews, K.: Are tag clouds useful for navigation? A network-theoretic analysis. Int. J. Soc. Comput. Cyber-Phys. Syst. 1(1), 33–55 (2011)CrossRef
41.
Heymann, P., Garcia-Molina, H.: Collaborative creation of communal hierarchical taxonomies in social tagging systems. Technical report 2006–2010, Stanford University, April 2006
42.
Heymann, P., Paepcke, A., Garcia-Molina, H.: Tagging human knowledge. In: Proceedings of the Third ACM International Conference on Web Search and Data Mining, WSDM 2010, pp. 51–60. ACM, New York (2010)
43.
Hong, L., Chi, E.H., Budiu, R., Pirolli, P., Nelson, L.: SparTag.us: a low cost tagging system for foraging of web content. In: Proceedings of the Working Conference on Advanced Visual Interfaces, AVI 2008, pp. 65–72. ACM, New York (2008)
44.
45.
46.
Jaffe, A., Naaman, M., Tassa, T., Davis, M.: Generating summaries and visualization for large collections of geo-referenced photographs. In: Proceedings of the 8th ACM International Workshop on Multimedia Information Retrieval, MIR 2006, pp. 89–98. ACM, New York (2006)
47.
Kammerer, Y., Nairn, R., Pirolli, P., Chi, E.H.: Signpost from the masses: learning effects in an exploratory social tag search browser. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2009, pp. 625–634. ACM, New York (2009)
48.
Kaser, O., Lemire, D.: Tag-cloud drawing: algorithms for cloud visualization. arXiv preprint arXiv:​0703109 (2007)
49.
Kleinberg, J.: Navigation in a small world. Nature 406(6798), 845 (2000)CrossRef
50.
Kleinberg, J.: The small-world phenomenon: an algorithmic perspective. In: Proceedings of the Thirty-second Annual ACM Symposium on Theory of Computing, pp. 163–170. ACM (2000)
51.
Kleinberg, J.: Small-world phenomena and the dynamics of information. Adv. Neural Inf. Process. syst. 1, 431–438 (2002)
52.
Körner, C., Benz, D., Hotho, A., Strohmaier, M., Stumme, G.: Stop thinking, start tagging: tag semantics emerge from collaborative verbosity. In: Proceedings of the 19th International Conference on World Wide Web, WWW 2010, pp. 521–530. ACM, New York (2010)
53.
Kuo, B.Y.L., Hentrich, T., Good, B.M., Wilkinson, M.D.: Tag clouds for summarizing web search results. In: Proceedings of the 16th International Conference on World Wide Web, WWW 2007, pp. 1203–1204. ACM, New York (2007)
54.
Lancichinetti, A., Fortunato, S., Kertész, J.: Detecting the overlapping and hierarchical community structure in complex networks. New J. Phys. 11(3), 033015 (2009)CrossRef
55.
Lee, B., Riche, N.H., Karlson, A.K., Carpendale, S.: Sparkclouds: visualizing trends in tag clouds. IEEE Trans. Vis. Comput. Graph. 16(6), 1182–1189 (2010)CrossRef
56.
Li, R., Bao, S., Yu, Y., Fei, B., Su, Z.: Towards effective browsing of large scale social annotations. In: Proceedings of the 16th International Conference on World Wide Web, WWW 2007, pp. 943–952. ACM, New York (2007)
57.
Li, Z., Tian, J.: Testing the suitability of Markov chains as web usage models. In: Proceedings 27th Annual International Computer Software and Applications Conference, COMPSAC 2003, pp. 356–361. IEEE (2003)
58.
Lin, Y.L., Brusilovsky, P., He, D.: Finding cultural heritage images through a dual-perspective navigation framework. Inf. Process. Manag. 52(5), 820–839 (2016)CrossRef
59.
60.
Lohmann, S., Ziegler, J., Tetzlaff, L.: Comparison of tag cloud layouts: task-related performance and visual exploration. In: Gross, T., Gulliksen, J., Kotzé, P., Oestreicher, L., Palanque, P., Prates, R.O., Winckler, M. (eds.) INTERACT 2009. LNCS, vol. 5726, pp. 392–404. Springer, Heidelberg (2009). https://​doi.​org/​10.​1007/​978-3-642-03655-2_​43CrossRef
61.
Macgregor, G., McCulloch, E.: Collaborative tagging as a knowledge organisation and resource discovery tool. Libr. Rev. 55(5), 291–300 (2006)CrossRef
62.
63.
Miao, G., Tao, S., Cheng, W., Moulic, R., Moser, L.E., Lo, D., Yan, X.: Understanding task-driven information flow in collaborative networks. In: Proceedings of the 21st International Conference on World Wide Web, WWW 2012, pp. 849–858. ACM, New York (2012)
64.
Mika, P.: Ontologies are us: a unified model of social networks and semantics. Web Semant. Sci. Serv. Agents World Wide Web 5(1), 5–15 (2007)CrossRef
65.
Millen, D.R., Feinberg, J.: Using social tagging to improve social navigation. In: Workshop on the Social Navigation and Community based Adaptation Technologies (2006)
66.
Muchnik, L., Itzhack, R., Solomon, S., Louzoun, Y.: Self-emergence of knowledge trees: extraction of the Wikipedia hierarchies. Phys. Rev. E 76(1), 016106 (2007)CrossRef
67.
Navarro Bullock, B., Hotho, A., Stumme, G.: Accessing information with tags: search and ranking. In: Brusilovsky, P., He, D. (eds.) Social Information Access. LNCS, vol. 10100, pp. 310–343. Springer, Cham (2018)
68.
Pirolli, P.: An elementary social information foraging model. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2009, pp. 605–614. ACM, New York (2009)
69.
Pirolli, P., Card, S.: Information foraging. Psychol. Rev. 106(4), 643 (1999)CrossRef
70.
71.
Plangprasopchok, A., Lerman, K., Getoor, L.: From saplings to a tree: integrating structured metadata via relational affinity propagation. In: Proceedings of the AAAI Workshop on Statistical Relational AI, July 2010
72.
Ramage, D., Heymann, P., Manning, C.D., Garcia-Molina, H.: Clustering the tagged web. In: Proceedings of the Second ACM International Conference on Web Search and Data Mining, WSDM 2009, pp. 54–63. ACM, New York (2009)
73.
Rivadeneira, A.W., Gruen, D.M., Muller, M.J., Millen, D.R.: Getting our head in the clouds: toward evaluation studies of tagclouds. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2007, pp. 995–998. ACM, New York (2007)
74.
Russell, T.: Cloudalicious: Folksonomy over time. In: Proceedings of the 6th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 2006, p. 364. ACM, New York (2006)
75.
76.
Schmitz, P.: Inducing ontology from flickr tags. In: Collaborative Web Tagging Workshop at WWW 2006, vol. 50, Edinburgh, Scotland (2006)
77.
Seifert, C., Kump, B., Kienreich, W., Granitzer, G., Granitzer, M.: On the beauty and usability of tag clouds. In: 12th International Conference Information Visualisation, 2008, IV 2008, pp. 17–25. IEEE (2008)
78.
Sinclair, J., Cardew-Hall, M.: The folksonomy tag cloud: when is it useful? J. Inf. Sci. 34(1), 15–29 (2008)CrossRef
79.
Singer, P., Helic, D., Hotho, A., Strohmaier, M.: Hyptrails: a bayesian approach for comparing hypotheses about human trails on the web. In: Proceedings of the 24th International Conference on World Wide Web, International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland WWW 2015, pp. 1003–1013 (2015)
80.
Skoutas, D., Alrifai, M.: Tag clouds revisited. In: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, CIKM 2011, pp. 221–230. ACM, New York (2011)
81.
82.
Trattner, C., Lin, Y., Parra, D., Yue, Z., Real, W., Brusilovsky, P.: Evaluating tag-based information access in image collections. In: Proceedings of the 23rd ACM Conference on Hypertext and Social Media, HT 2012, pp. 113–122. ACM, New York (2012)
83.
Tufte, E.R.: Beautiful Evidence. Graphis Press, New York City (2006)
84.
Venetis, P., Koutrika, G., Garcia-Molina, H.: On the selection of tags for tag clouds. In: Proceedings of the Fourth ACM International Conference on Web Search and Data Mining, WSDM 2011, pp. 835–844. ACM, New York (2011)
85.
Viegas, F.B., Wattenberg, M., Feinberg, J.: Participatory visualization with wordle. IEEE Trans. Vis. Comput. Graph. 15(6), 1137–1144 (2009)CrossRef
86.
Vig, J., Sen, S.: Computing the tag genome. Technical report, 10 September 2010
87.
Vig, J., Sen, S., Riedl, J.: Navigating the tag genome. In: Proceedings of the 16th International Conference on Intelligent User Interfaces, IUI 2011, pp. 93–102. ACM, New York (2011)
88.
Vig, J., Sen, S., Riedl, J.: The tag genome: encoding community knowledge to support novel interaction. ACM Trans. Interact. Intell. Syst. (TiiS) 2(3), 13 (2012)
89.
90.
Watts, D.J., Dodds, P.S., Newman, M.E.: Identity and search in social networks. Science 296(5571), 1302–1305 (2002)CrossRef
91.
Watts, D.J., Strogatz, S.H.: Collective dynamics of small-worldnetworks. Nature 393(6684), 440–442 (1998)CrossRefMATH
92.
West, R., Leskovec, J.: Human wayfinding in information networks. In: Proceedings of the 21st International Conference on World Wide Web, WWW 2012, pp. 619–628. ACM, New York, (2012)
93.
Zhong, S.: Efficient online spherical k-means clustering. In: Proceedings, 2005 IEEE International Joint Conference on Neural Networks, IJCNN 2005, vol. 5, pp. 3180–3185. IEEE (2005)
94.
95.
Zubiaga, A., García-Plaza, A.P., Fresno, V., Martínez, R.: Content-based clustering for tag cloud visualization. In: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2009, pp. 316–319. IEEE Computer Society, Washington (2009)
Metadaten
Titel
Tag-Based Navigation and Visualization
verfasst von
Dimitar Dimitrov
Denis Helic
Markus Strohmaier
Copyright-Jahr
2018
Buch
Social Information Access

Print ISBN: 978-3-319-90091-9

Electronic ISBN: 978-3-319-90092-6

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-90092-6_6