BibSonomy publications for /user/mstrohmFri Oct 28 15:26:50 CEST 2011New York, NY, USAProceedings of the 12th international conference on Intelligent user interfaces32--41IUI '07SuggestBot: using intelligent task routing to help people find work in wikipedia2007TOREAD knowledge-production wikis Member-maintained communities ask their users to perform tasks the community needs. From Slashdot, to IMDb, to Wikipedia, groups with diverse interests create community-maintained artifacts of lasting value (CALV) that support the group's main purpose and provide value to others. Said communities don't help members find work to do, or do so without regard to individual preferences, such as Slashdot assigning meta-moderation randomly. Yet social science theory suggests that reducing the cost and increasing the personal value of contribution would motivate members to participate more.We present SuggestBot, software that performs intelligent task routing (matching people with tasks) in Wikipedia. SuggestBot uses broadly applicable strategies of text analysis, collaborative filtering, and hyperlink following to recommend tasks. SuggestBot's intelligent task routing increases the number of edits by roughly four times compared to suggesting random articles. Our contributions are: 1) demonstrating the value of intelligent task routing in a real deployment; 2) showing how to do intelligent task routing; and 3) sharing our experience of deploying a tool in Wikipedia, which offered both challenges and opportunities for research.Wed Aug 17 23:13:30 CEST 2011Cognitive Psychology49--96Categorization and reasoning among tree experts: Do all roads lead to Rome?321997MUSTREAD categorization classification cognition folksonomies Wed Aug 17 22:16:03 CEST 2011Reflections247--59Community knowledge sharing in practice: the Eureka story42002FKM MUSTREAD course knowledge-acquisition knowledge-management knowledge-transfer Thu Aug 04 19:30:46 CEST 201120th ACM Conference on Information and Knowledge Management (CIKM 2011), Glasgow, UKBuilding Directories for Social Tagging Systems2011algorithms myown navigability tagging taggingsurvey Thu Jun 23 23:07:21 CEST 2011Sybil-resilient online content rating2009PRELIMINARY-BIBTEX networks social-factors web-science Fri Jan 28 00:29:30 CET 201120th International World Wide Web Conference (WWW2011), Hyderabad, India, March 28 - April 1, ACMPragmatic Evaluation of Folksonomies2011folksonomy knowledge-acquisition myown semantic tagging taggingsurvey Sat Nov 13 16:46:11 CET 2010Engineering societies in the agents world1--18{Engineering social order}2000MUSTREAD agents networks social Wed Nov 10 10:50:20 CET 2010Atlantic MonthlyJuly{As We May Think}1945cognition hypertext Wed Nov 10 10:20:34 CET 2010science59961194{The Spread of Behavior in an Online Social Network Experiment}3292010MUSTREAD behavior networks social Sun Oct 31 12:40:31 CET 2010Proceedings of the Conference on Data Mining and Data Warehouses (SiKDD 2005)166--170{A survey of ontology evaluation techniques}2005evaluation folksonomies knowledge-acquisition ontologies taggingsurvey Sat Oct 30 11:59:24 CEST 2010Naturecite arxiv:0709.0303 Navigability of Complex Networks2007MUSTREAD networks theory Routing information through networks is a universal phenomenon in both natural and manmade complex systems. When each node has full knowledge of the global network connectivity, finding short communication paths is merely a matter of distributed computation. However, in many real networks nodes communicate efficiently even without such global intelligence. Here we show that the peculiar structural characteristics of many complex networks support efficient communication without global knowledge. We also describe a general mechanism that explains this connection between network structure and function. This mechanism relies on the presence of a metric space hidden behind an observable network. Our findings suggest that real networks in nature have underlying metric spaces that remain undiscovered. Their discovery would have practical applications ranging from routing in the Internet and searching social networks, to studying information flows in neural, gene regulatory networks, or signaling pathways. Fri Jun 25 12:09:08 CEST 2010{Networks, Crowds, and Markets: Reasoning About a Highly Connected World}2010algorithms books networks Sat May 08 14:16:53 CEST 2010Innovations in Information Technology1--5{Measuring the semantic value of folksonomies}2006MUSTREAD folksonomies motivation value Sat May 01 05:47:02 CEST 2010New York, NY, USAHT '07: Proceedings of the eighteenth conference on Hypertext and hypermedia179--180Back to the future with hypertext: a tale of two or three conferences2007MUSTREAD historical web-science Tue Apr 27 17:23:00 CEST 2010Linked Data on the Web Workshop (LDOW2010) at WWW'2010{Weaving the Pedantic Web}2010navigability semantic Mon Apr 19 19:11:25 CEST 2010Proc. of the Semantic Search 2010 Workshop (SemSearch2010)aprilThe Wisdom in Tweetonomies: Acquiring Latent Conceptual Structures from Social Awareness Streams2010folksonomy myown networks social tagging twitter taggingsurvey Sun Mar 28 12:48:20 CEST 2010Toronto, Canada21st ACM SIGWEB Conference on Hypertext and Hypermedia (HT 2010)JuneOf Categorizers and Describers: An Evaluation of Quantitative Measures for Tagging Motivation2010agents folksonomy goals mining motivation social tagging myown Fri Mar 19 16:58:07 CET 2010International AAAI Conference on Weblogs and Social Media (ICWSM2010), Washington, DC, USA, May 23-26Why do users tag? Detecting users’ motivation for tagging in social tagging systems2010motivation myown social-factors tagging taggingsurvey Fri Mar 19 16:48:36 CET 2010New York, NY, USAWWW '09: Proceedings of the 18th international conference on World wide web781--790Constructing folksonomies from user-specified relations on flickr2009categorization tagging taxonomy-development taggingsurvey Automatic folksonomy construction from tags has attracted much attention recently. However, inferring hierarchical relations between concepts from tags has a drawback in that it is difficult to distinguish between more popular and more general concepts. Instead of tags we propose to use user-specified relations for learning folksonomy. We explore two statistical frameworks for aggregating many shallow individual hierarchies, expressed through the collection/set relations on the social photosharing site Flickr, into a common deeper folksonomy that reflects how a community organizes knowledge. Our approach addresses a number of challenges that arise while aggregating information from diverse users, namely noisy vocabulary, and variations in the granularity level of the concepts expressed. Our second contribution is a method for automatically evaluating learned folksonomy by comparing it to a reference taxonomy, e.g., the Web directory created by the Open Directory Project. Our empirical results suggest that user-specified relations are a good source of evidence for learning folksonomies.Wed Mar 17 08:51:06 CET 2010Journal of The Royal Society Interface15707-719{A general framework for analysing diversity in science, technology and society}42007categorization classification cognition tools This paper addresses the scope for more integrated general analysis of diversity in science, technology and society. It proposes a framework recognizing three necessary but individually insufficient properties of diversity. Based on 10 quality criteria, it suggests a general quantitative non-parametric diversity heuristic. This allows the systematic exploration of diversity under different perspectives, including divergent conceptions of relevant attributes and contrasting weightings on different diversity properties. It is shown how this heuristic may be used to explore different possible trade-offs between diversity and other aspects of interest, including portfolio interactions. The resulting approach offers a way to be more systematic and transparent in the treatment of scientific and technological diversity in a range of fields, including conservation management, research governance, energy policy and sustainable innovation.