ER - TY - JOUR AU - Golder, Scott A. AU - Huberman, Bernardo A. T1 - Usage patterns of collaborative tagging systems JO - Journal of Information Science PY - 2006/ VL - 32 IS - 2 SP - 198 EP - 208 UR - http://jis.sagepub.com/cgi/content/abstract/32/2/198 M3 - 10.1177/0165551506062337 KW - analysis KW - collaborative KW - patterns KW - purpose KW - systems KW - tagging KW - taggingsurvey KW - usage L1 - SN - N1 - Usage patterns of collaborative tagging systems -- Golder and Huberman 32 (2): 198 -- Journal of Information Science N1 - AB - Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs and other content. In this paper we analyze the structure of collaborative tagging systems as well as their dynamic aspects. Specifically, we discovered regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given URL. We also present a dynamic model of collaborative tagging that predicts these stable patterns and relates them to imitation and shared knowledge. ER - TY - CHAP AU - Berendt, Bettina AU - Hotho, Andreas AU - Stumme, Gerd A2 - Kargupta, Hillol A2 - Joshi, Anupam A2 - Sivakumar, Krishnamoorthy A2 - Yesha, Yelena T1 - Usage Mining for and on the Semantic Web T2 - Data Mining Next Generation Challenges and Future Directions PB - AAAI Press CY - Boston PY - 2004/ VL - IS - SP - 461 EP - 481 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2004/berendt04usage.pdf M3 - KW - 2004 KW - itegpub KW - l3s KW - mining KW - myown KW - semantic KW - usage KW - web L1 - SN - 0-262-61203-8 N1 - N1 - AB - Semantic Web Mining aims at combining the two fast-developing
research areas Semantic Web and Web Mining.
Web Mining aims at discovering insights about the meaning of Web
resources and their usage. Given the primarily syntactical nature
of data Web mining operates on, the discovery of meaning is
impossible based on these data only. Therefore, formalizations of
the semantics of Web resources and navigation behavior are
increasingly being used. This fits exactly with the aims of the
Semantic Web: the Semantic Web enriches the WWW by
machine-processable information which supports the user in his
tasks. In this paper, we discuss the interplay of the Semantic Web
with Web Mining, with a specific focus on usage mining. ER - TY - CHAP AU - Berendt, Bettina AU - Hotho, Andreas AU - Stumme, Gerd A2 - Kargupta, Hillol A2 - Joshi, Anupam A2 - Sivakumar, Krishnamoorthy A2 - Yesha, Yelena T1 - Usage Mining for and on the Semantic Web T2 - Data Mining Next Generation Challenges and Future Directions PB - AAAI Press CY - Boston PY - 2004/ VL - IS - SP - 461 EP - 481 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2004/berendt04usage.pdf M3 - KW - 2004 KW - itegpub KW - l3s KW - mining KW - myown KW - semantic KW - usage KW - web L1 - SN - 0-262-61203-8 N1 - Publications of Gerd Stumme N1 - AB - Semantic Web Mining aims at combining the two fast-developing
research areas Semantic Web and Web Mining.
Web Mining aims at discovering insights about the meaning of Web
resources and their usage. Given the primarily syntactical nature
of data Web mining operates on, the discovery of meaning is
impossible based on these data only. Therefore, formalizations of
the semantics of Web resources and navigation behavior are
increasingly being used. This fits exactly with the aims of the
Semantic Web: the Semantic Web enriches the WWW by
machine-processable information which supports the user in his
tasks. In this paper, we discuss the interplay of the Semantic Web
with Web Mining, with a specific focus on usage mining. ER - TY - CONF AU - Stumme, G. AU - Berendt, B. AU - Hotho, A. A2 - T1 - Usage Mining for and on the Semantic Web T2 - Proc. NSF Workshop on Next Generation Data Mining PB - CY - Baltimore PY - 2002/november M2 - VL - IS - SP - 77 EP - 86 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2002/NSF-NGDM02.pdf M3 - KW - 2002 KW - mining KW - myown KW - semantic KW - usage KW - web L1 - SN - N1 - Publications of Gerd Stumme N1 - AB - ER - TY - CHAP AU - Berendt, Bettina AU - Hotho, Andreas AU - Stumme, Gerd A2 - Kargupta, Hillol A2 - Joshi, Anupam A2 - Sivakumar, Krishnamoorthy A2 - Yesha, Yelena T1 - Usage Mining for and on the Semantic Web T2 - Data Mining Next Generation Challenges and Future Directions PB - AAAI Press CY - Boston PY - 2004/ VL - IS - SP - 461 EP - 481 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2004/berendt04usage.pdf M3 - KW - iccs_example KW - mining KW - semantic KW - trias_example KW - usage KW - web L1 - SN - 0-262-61203-8 N1 - N1 - AB - Semantic Web Mining aims at combining the two fast-developing
research areas Semantic Web and Web Mining.
Web Mining aims at discovering insights about the meaning of Web
resources and their usage. Given the primarily syntactical nature
of data Web mining operates on, the discovery of meaning is
impossible based on these data only. Therefore, formalizations of
the semantics of Web resources and navigation behavior are
increasingly being used. This fits exactly with the aims of the
Semantic Web: the Semantic Web enriches the WWW by
machine-processable information which supports the user in his
tasks. In this paper, we discuss the interplay of the Semantic Web
with Web Mining, with a specific focus on usage mining. ER - TY - CONF AU - Stumme, G. AU - Berendt, B. AU - Hotho, A. A2 - T1 - Usage Mining for and on the Semantic Web T2 - Proc. NSF Workshop on Next Generation Data Mining PB - CY - Baltimore PY - 2002/november M2 - VL - IS - SP - 77 EP - 86 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2002/NSF-NGDM02.pdf M3 - KW - iccs_example KW - mining KW - semantic KW - trias_example KW - usage KW - web L1 - SN - N1 - Preliminary version of http://www.bibsonomy.org/bibtex/0a3c7992f2f6d8ecf7adc04aa6c2d5a22/stumme N1 - AB - ER - TY - CONF AU - Jones, Steve AU - Cunningham, Sally Jo AU - McNab, Rodger A2 - T1 - Usage analysis of a digital library T2 - Proceedings of the third ACM conference on Digital libraries PB - ACM CY - New York, NY, USA PY - 1998/ M2 - VL - IS - SP - 293 EP - 294 UR - http://doi.acm.org/10.1145/276675.276739 M3 - 10.1145/276675.276739 KW - analysis KW - digital KW - library KW - logs KW - mining KW - usage KW - weblog L1 - SN - 0-89791-965-3 N1 - Usage analysis of a digital library N1 - AB - ER - TY - CONF AU - Schneider, Fabian AU - Feldmann, Anja AU - Krishnamurthy, Balachander AU - Willinger, Walter A2 - T1 - Understanding Online Social Network Usage from a Network Perspective T2 - Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement Conference PB - ACM CY - New York, NY, USA PY - 2009/ M2 - VL - IS - SP - 35 EP - 48 UR - http://doi.acm.org/10.1145/1644893.1644899 M3 - 10.1145/1644893.1644899 KW - analysis KW - behavior KW - network KW - social KW - usage L1 - SN - 978-1-60558-771-4 N1 - Understanding online social network usage from a network perspective N1 - AB - Online Social Networks (OSNs) have already attracted more than half a billion users. However, our understanding of which OSN features attract and keep the attention of these users is poor. Studies thus far have relied on surveys or interviews of OSN users or focused on static properties, e. g., the friendship graph, gathered via sampled crawls. In this paper, we study how users actually interact with OSNs by extracting clickstreams from passively monitored network traffic. Our characterization of user interactions within the OSN for four different OSNs (Facebook, LinkedIn, Hi5, and StudiVZ) focuses on feature popularity, session characteristics, and the dynamics within OSN sessions. We find, for example, that users commonly spend more than half an hour interacting with the OSNs while the byte contributions per OSN session are relatively small. ER - TY - JOUR AU - Nicholas, David AU - Huntington, Paul AU - Watkinson, Anthony T1 - Scholarly journal usage: the results of deep log analysis JO - Journal of Documentation PY - 2005/ VL - 61 IS - 2 SP - 248 EP - 280 UR - http://www.emeraldinsight.com/journals.htm?articleid=1465024&show=abstract M3 - KW - Scholarly KW - analysis KW - deep KW - journal KW - log KW - mining KW - usage KW - weblog L1 - SN - N1 - Emerald | Journal of Documentation | Scholarly journal usage: the results of deep log analysis N1 - AB - ER - TY - CONF AU - Zoller, Daniel AU - Doerfel, Stephan AU - Jäschke, Robert AU - Stumme, Gerd AU - Hotho, Andreas A2 - T1 - On Publication Usage in a Social Bookmarking System T2 - Proceedings of the 2015 ACM Conference on Web Science PB - CY - PY - 2015/ M2 - VL - IS - SP - EP - UR - M3 - KW - 2015 KW - altmetrics KW - bookmarking KW - impact KW - myown KW - publication KW - social KW - usage L1 - SN - N1 - N1 - AB - Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations. ER - TY - CONF AU - Abrams, David AU - Baecker, Ron AU - Chignell, Mark A2 - T1 - Information archiving with bookmarks: personal Web space construction and organization T2 - Proceedings of the SIGCHI Conference on Human Factors in Computing Systems PB - ACM Press/Addison-Wesley Publishing Co. CY - New York, NY, USA PY - 1998/ M2 - VL - IS - SP - 41 EP - 48 UR - http://dx.doi.org/10.1145/274644.274651 M3 - 10.1145/274644.274651 KW - analysis KW - bookmarking KW - folksonomy KW - log KW - social KW - usage L1 - SN - 0-201-30987-4 N1 - Information archiving with bookmarks N1 - AB - ER - TY - JOUR AU - Glushko, Robert J. AU - Maglio, Paul P. AU - Matlock, Teenie AU - Barsalou, Lawrence W. T1 - Categorization in the wild JO - Trends in Cognitive Sciences PY - 2008/ VL - 12 IS - 4 SP - 129 EP - 135 UR - http://www.sciencedirect.com/science/article/pii/S1364661308000557 M3 - http://dx.doi.org/10.1016/j.tics.2008.01.007 KW - tagging KW - usage L1 - SN - N1 - Categorization in the wild N1 - AB - In studying categorization, cognitive science has focused primarily on cultural categorization, ignoring individual and institutional categorization. Because recent technological developments have made individual and institutional classification systems much more available and powerful, our understanding of the cognitive and social mechanisms that produce these systems is increasingly important. Furthermore, key aspects of categorization that have received little previous attention emerge from considering diverse types of categorization together, such as the social factors that create stability in classification systems, and the interoperability that shared conceptual systems establish between agents. Finally, the profound impact of recent technological developments on classification systems indicates that basic categorization mechanisms are highly adaptive, producing new classification systems as the situations in which they operate change. ER - TY - JOUR AU - Haustein, Stefanie AU - Siebenlist, Tobias T1 - Applying social bookmarking data to evaluate journal usage JO - Journal of Informetrics PY - 2011/ VL - 5 IS - 3 SP - 446 EP - 457 UR - http://www.sciencedirect.com/science/article/pii/S1751157711000393 M3 - 10.1016/j.joi.2011.04.002 KW - bookmarking KW - citation KW - journal KW - social KW - toread KW - usage L1 - SN - N1 - ScienceDirect.com - Journal of Informetrics - Applying social bookmarking data to evaluate journal usage N1 - AB - Web 2.0 technologies are finding their way into academics: specialized social bookmarking services allow researchers to store and share scientific literature online. By bookmarking and tagging articles, academic prosumers generate new information about resources, i.e. usage statistics and content description of scientific journals. Given the lack of global download statistics, the authors propose the application of social bookmarking data to journal evaluation. For a set of 45 physics journals all 13,608 bookmarks from CiteULike, Connotea and BibSonomy to documents published between 2004 and 2008 were analyzed. This article explores bookmarking data in STM and examines in how far it can be used to describe the perception of periodicals by the readership. Four basic indicators are defined, which analyze different aspects of usage: Usage Ratio, Usage Diffusion, Article Usage Intensity and Journal Usage Intensity. Tags are analyzed to describe a reader-specific view on journal content. ER - TY - JOUR AU - Duarte Torres, Sergio AU - Weber, Ingmar AU - Hiemstra, Djoerd T1 - Analysis of Search and Browsing Behavior of Young Users on the Web JO - ACM Transactions on the Web PY - 2014/03 VL - 8 IS - 2 SP - 7:1 EP - 7:54 UR - http://doi.acm.org/10.1145/2555595 M3 - 10.1145/2555595 KW - analysis KW - behavior KW - children KW - usage KW - weblog L1 - SN - N1 - Analysis of Search and Browsing Behavior of Young Users on the Web N1 - AB - The Internet is increasingly used by young children for all kinds of purposes. Nonetheless, there are not many resources especially designed for children on the Internet and most of the content online is designed for grown-up users. This situation is problematic if we consider the large differences between young users and adults since their topic interests, computer skills, and language capabilities evolve rapidly during childhood. There is little research aimed at exploring and measuring the difficulties that children encounter on the Internet when searching for information and browsing for content. In the first part of this work, we employed query logs from a commercial search engine to quantify the difficulties children of different ages encounter on the Internet and to characterize the topics that they search for. We employed query metrics (e.g., the fraction of queries posed in natural language), session metrics (e.g., the fraction of abandoned sessions), and click activity (e.g., the fraction of ad clicks). The search logs were also used to retrace stages of child development. Concretely, we looked for changes in interests (e.g., the distribution of topics searched) and language development (e.g., the readability of the content accessed and the vocabulary size). In the second part of this work, we employed toolbar logs from a commercial search engine to characterize the browsing behavior of young users, particularly to understand the activities on the Internet that trigger search. We quantified the proportion of browsing and search activity in the toolbar sessions and we estimated the likelihood of a user to carry out search on the Web vertical and multimedia verticals (i.e., videos and images) given that the previous event is another search event or a browsing event. We observed that these metrics clearly demonstrate an increased level of confusion and unsuccessful search sessions among children. We also found a clear relation between the reading level of the clicked pages and characteristics of the users such as age and educational attainment. In terms of browsing behavior, children were found to start their activities on the Internet with a search engine (instead of directly browsing content) more often than adults. We also observed a significantly larger amount of browsing activity for the case of teenager users. Interestingly we also found that if children visit knowledge-related Web sites (i.e., information-dense pages such as Wikipedia articles), they subsequently do more Web searches than adults. Additionally, children and especially teenagers were found to have a greater tendency to engage in multimedia search, which calls to improve the aggregation of multimedia results into the current search result pages. ER - TY - CHAP AU - Lorince, Jared AU - Joseph, Kenneth AU - Todd, PeterM. A2 - Agarwal, Nitin A2 - Xu, Kevin A2 - Osgood, Nathaniel T1 - Analysis of Music Tagging and Listening Patterns: Do Tags Really Function as Retrieval Aids? T2 - Social Computing, Behavioral-Cultural Modeling, and Prediction PB - Springer International Publishing CY - PY - 2015/ VL - 9021 IS - SP - 141 EP - 152 UR - http://dx.doi.org/10.1007/978-3-319-16268-3_15 M3 - 10.1007/978-3-319-16268-3_15 KW - folksonomy KW - last.fm KW - retrieval KW - tagging KW - usage L1 - SN - 978-3-319-16267-6 N1 - Analysis of Music Tagging and Listening Patterns: Do Tags Really Function as Retrieval Aids? - Springer N1 - AB - In collaborative tagging systems, it is generally assumed that users assign tags to facilitate retrieval of content at a later time. There is, however, little behavioral evidence that tags actually serve this purpose. Using a large-scale dataset from the social music website Last.fm, we explore how patterns of music tagging and subsequent listening interact to determine if there exist measurable signals of tags functioning as retrieval aids. Specifically, we describe our methods for testing if the assignment of a tag tends to lead to an increase in listening behavior. Results suggest that tagging, on average, leads to only very small increases in listening rates, and overall the data do ER - TY - JOUR AU - Zhang, Dell AU - Dong, Yisheng T1 - A novel Web usage mining approach for search engines JO - Computer Networks PY - 2002/06 VL - 39 IS - 3 SP - 303 EP - 310 UR - http://www.sciencedirect.com/science/article/B6VRG-45H0GV7-5/2/16726cebdcde67ba7aeb95cc91e797bf M3 - 10.1016/S1389-1286(02)00211-6 KW - engine KW - mining KW - search KW - usage KW - web L1 - SN - N1 - N1 - AB - Web usage mining can be very useful to search engines. This paper proposes a novel effective approach to exploit the relationships among users, queries and resources based on the search engine's log. How this method can be applied is illustrated by a Chinese image search engine. ER -