http://www.bibsonomy.org/burst/tag/snaBibSonomy BuRST Feed for /tag/sna2008-08-21T12:47:02+02:00AAAS - Science and Human Rights Programhttp://www.bibsonomy.org/bibtex/22353cbfaa60776cfe6848afb265054d0/falkowskifalkowski2008-08-04T18:24:31+02:00SNA Applications Report <span style="color:#555555;">Skye <a href="http://www.bibsonomy.org/author/Bender-deMoll">Bender-deMoll</a> </span>(<em>2008</em>)Mon Aug 04 18:24:31 CEST 2008Potential Human Rights Uses of Network Analysis and Mapping: A report to the Science and Human Rights Program of the American Association for the Advancement of Science 2008SNA Applications Report [0807.4052] Modularity clustering is force-directed layouthttp://www.bibsonomy.org/bibtex/20186031133dc122ffd6ff33ded32c911/stummestumme2008-07-31T11:57:32+02:00sna network modularity communities community graph layout clustering <span style="color:#555555;">Andreas <a href="http://www.bibsonomy.org/author/Noack">Noack</a> </span>(<em>2008</em>)Thu Jul 31 11:57:32 CEST 2008Modularity clustering is force-directed layout2008sna network modularity communities community graph layout clustering Two natural and widely used representations for the community structure of networks are clusterings, which partition the vertex set into disjoint subsets, and layouts, which assign the vertices to positions in a metric space. This paper unifies prominent characterizations of layout quality and clustering quality, by showing that energy models of pairwise attraction and repulsion subsume Newman and Girvan's modularity measure. Layouts with optimal energy are relaxations of, and are thus consistent with, clusterings with optimal modularity, which is of practical relevance because both representations are complementary and often used together.contains a set of interesting references to "intent" literaturehttp://www.bibsonomy.org/bibtex/25c4bc55106b6eed14768ecbbeba2e687/mkroellmkroell2008-07-07T19:52:10+02:00social SNA communities commonsense toread <span style="color:#555555;">A. <a href="http://www.bibsonomy.org/author/Java">Java</a> and X. <a href="http://www.bibsonomy.org/author/Song">Song</a> and T. <a href="http://www.bibsonomy.org/author/Finin">Finin</a> and B. <a href="http://www.bibsonomy.org/author/Tseng">Tseng</a> </span><em>July2007. </em><em>Simple description of Twitter . </em>Mon Jul 07 19:52:10 CEST 2008JulySimple description of TwitterWhy We Twitter: Understanding Microblogging Usage and Communities2007social SNA communities commonsense toread http://www.bibsonomy.org/bibtex/235df9e6362e8c3180a88af6e41357d2b/kochmkochm2008-06-27T10:36:46+02:00socialsoftware analysis socialnetwork sna enterprise2.0 <span style="color:#555555;">Claudia <a href="http://www.bibsonomy.org/author/Müller">M&#252;ller</a> and Norbert <a href="http://www.bibsonomy.org/author/Gronau">Gronau</a> </span><em>Web 2.0 in der Unternehmenspraxis, </em><em>Oldenbourg, </em><em>M&#252;nchen, </em>(<em>2008</em>)Fri Jun 27 10:36:46 CEST 2008MünchenWeb 2.0 in der Unternehmenspraxis256-266Untersuchung virtueller Informationsräume auf Basis der Netzwerkanalyse2008socialsoftware analysis socialnetwork sna enterprise2.0 Graph building as a mining activityhttp://www.bibsonomy.org/bibtex/253fb57b6c54debd70ee873751acfcf15/mkroellmkroell2008-06-25T20:40:17+02:00SNA toread networks graph mining framework <span style="color:#555555;">Antonio <a href="http://www.bibsonomy.org/author/Badia">Badia</a> and Mehmed <a href="http://www.bibsonomy.org/author/Kantardzic">Kantardzic</a> </span><em>LinkKDD '05: Proceedings of the 3rd international workshop on Link discovery, </em><em>page17--24. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2005</em>)Wed Jun 25 20:40:17 CEST 2008New York, NY, USALinkKDD '05: Proceedings of the 3rd international workshop on Link discovery17--24Graph building as a mining activity: finding links in the small2005SNA toread networks graph mining framework Many analysis of data proceed by building a graph out of the data set and then using social network theory and similar tools on the result. However, there is no theory concerning the construction of the graph itself, even though this is a very important process. In this paper, we attempt to provide a framework in which the graph building process is formalized and studied. We show the parameters (choices) involved in constructing a graph from raw data, and propose some new ways to combine and analyze the data. We also argue the importance of this approach in several domain applications, including criminal/terrorist investigations.http://www.bibsonomy.org/bibtex/217bcda8a9e3d2215b54a687ed39ebc07/dflejterdflejter2008-06-06T15:45:42+02:00socialNetworks unevenness networks social SNA SAW2008 semantic SAW <span style="color:#555555;">Raf <a href="http://www.bibsonomy.org/author/Guns">Guns</a> </span><em>BIS 2008 Workshop Proceedings, </em><em>page21--30. </em>(<em>2008</em>)Fri Jun 06 15:45:42 CEST 2008BIS 2008 Workshop ProceedingsBIS:2008/221--30Unevenness in network properties on the social Semantic Web2008socialNetworks unevenness networks social SNA SAW2008 semantic SAW http://www.bibsonomy.org/bibtex/29632c170df74cc7c30c86ed558399d69/mstrohmmstrohm2008-04-22T10:13:08+02:00web-science SNA search networks <span style="color:#555555;">K. <a href="http://www.bibsonomy.org/author/Bryan">Bryan</a> and T. <a href="http://www.bibsonomy.org/author/Leise">Leise</a> </span><em>SIAM Review</em><em>48(3):569--581</em>(<em>2006</em>)Tue Apr 22 10:13:08 CEST 2008SIAM Review3569--581{The \$25,000,000,000 Eigenvector: The Linear Algebra behind Google}482006web-science SNA search networks http://www.bibsonomy.org/bibtex/2524d6c7e05430cc02e39bf51c3bbd779/mstrohmmstrohm2008-04-18T10:01:45+02:00networks MUSTREAD SNA <span style="color:#555555;">M.E.J. <a href="http://www.bibsonomy.org/author/Newman">Newman</a> </span><em>Physical Review E</em><em>74(3):36104</em>(<em>2006</em>)Fri Apr 18 10:01:45 CEST 2008Physical Review E336104{Finding community structure in networks using the eigenvectors of matrices}742006networks MUSTREAD SNA KNICOPhttp://www.bibsonomy.org/bibtex/242b79408ec3fc3a68482d2a66f15332a/xckukxckuk2008-04-13T15:33:20+02:00Tacit Organizational_Context Social_Network_Analysis Community_of_Practice Case_Study Community_Building KM IT_Platform Knowledge IT_Strategy SNA Virtual_Teams Face-to-Face Knowledge_Base Technology_and_Social_Issues Cost_Benefits_Analysis Knowledge_Sharing CoP Knowledge_Management Meetings <span style="color:#555555;">Mark Neff Laurence Lock <a href="http://www.bibsonomy.org/author/Lee">Lee</a> </span><em>Knowledge Networks: Innovation through Communities of Practice, </em><em>chapter 15, </em><em>IGI Global, </em><em>Hershey, PA, </em>(<em>2004</em>)Sun Apr 13 15:33:20 CEST 2008Hershey, PAKnowledge Networks: Innovation through Communities of Practice15165--183How Information Technologies Can Help Build and Sustain an Organization's Communities of Practice: Spanning the Socio-Technical Divide?2004Tacit Organizational_Context Social_Network_Analysis Community_of_Practice Case_Study Community_Building KM IT_Platform Knowledge IT_Strategy SNA Virtual_Teams Face-to-Face Knowledge_Base Technology_and_Social_Issues Cost_Benefits_Analysis Knowledge_Sharing CoP Knowledge_Management Meetings Communities of Practice (CoPs) are seen as a primary vehicle for knowledge sharing across large and disparate organizations. It is therefore expected that technology will play a critical role in enabling global CoPs. The usefulness of information technologies (IT) to support CoP activity in two large, but quite different, global organizations is analysed and common themes developed. BHP Billiton is one of the world's largest diversified resources company, with a strong industrial heritage and a mix of blue and white collar workers and levels of IT literacy. CSC is one the world's leading IT service providers, with a highly IT literate staff and a relatively sophisticated IT support environment. Both organizations could be considered early adopters of the CoP concept. This chapter tracks their evolution and the lessons learned along the way.KNICOPhttp://www.bibsonomy.org/bibtex/2f4e98d9ff9085f80df9c56a74740f191/xckukxckuk2008-04-13T15:33:20+02:00Values Boundaries Management_Issues Inter-Community_Communication IT_Industry Customer_Community_of_Practice Social_Networks Innovation CoP Expert_Seeking LPP Case_Study Identity Legitimate_Peripheral_Participation SNA Online_Community Social_Network_Analysis Knowledge_Sharing Organizational_Effectiveness <span style="color:#555555;">Anders <a href="http://www.bibsonomy.org/author/Lundkvist">Lundkvist</a> </span><em>Knowledge Networks: Innovation through Communities of Practice, </em><em>chapter 9, </em><em>IGI Global, </em><em>Hershey, PA, </em>(<em>2004</em>)Sun Apr 13 15:33:20 CEST 2008Hershey, PAKnowledge Networks: Innovation through Communities of Practice996--105User Networks as Sources of Innovation2004Values Boundaries Management_Issues Inter-Community_Communication IT_Industry Customer_Community_of_Practice Social_Networks Innovation CoP Expert_Seeking LPP Case_Study Identity Legitimate_Peripheral_Participation SNA Online_Community Social_Network_Analysis Knowledge_Sharing Organizational_Effectiveness In the computer and software business, it is common practice to involve users in problem solving and sharing of experiences, not only between a company and individual users but also between groups of users. Although problem solving and enabling customer support has gained some attention in recent years, a more intriguing thought would address users as a source of innovation. What if users themselves, or in interaction with other users, would, in addition to solving specific problems, also develop and share new knowledge that influences products within companies. In connection with this notion is the question as to how companies can come to relate to these networks of users. The empirical case study in this chapter was generated from a long-term study during 1998-1999 with Cisco Systems and the company's groups of users. Of particular interest to this study was the use of the Cisco newsgroup, which is available on the Internet. The conceptual framework was generated from the emerging theory of Communities of Practice (CoPs). By using this framework, user networks were recognised as peripheral and yet vital sites of innovation. This implies new strategies for management of innovation as the creation of spaces for interaction with and between users and addressing networks rather than individual users.KNICOPhttp://www.bibsonomy.org/bibtex/2299c6b3325b41ad02a19f9b7a2356a65/xckukxckuk2008-04-13T15:33:20+02:00Virtual_Organizations Virtual_Teams CoP Benefits Organizational_Effectiveness Change_Management Knowledge_Management Cost_Benefits_Analysis Management_Issues Community_Building Organizational_Learning Explicit_Knowledge SNA Social_Networks Tacit_Knowledge Organizational_Knowledge KM Information_Value Human_Resources Finance Community_of_Practice Social_Network_Analysis Knowledge_Utilization Ethnographic_Study Social_Capital <span style="color:#555555;">David R. <a href="http://www.bibsonomy.org/author/Millen Michael A. Fontaine">Millen Michael A. Fontaine</a> </span><em>Knowledge Networks: Innovation through Communities of Practice, </em><em>chapter 1, </em><em>IGI Global, </em><em>Hershey, PA, </em>(<em>2004</em>)Sun Apr 13 15:33:20 CEST 2008Hershey, PAKnowledge Networks: Innovation through Communities of Practice11--13Understanding the Benefits and Impact of Communities of Practice2004Virtual_Organizations Virtual_Teams CoP Benefits Organizational_Effectiveness Change_Management Knowledge_Management Cost_Benefits_Analysis Management_Issues Community_Building Organizational_Learning Explicit_Knowledge SNA Social_Networks Tacit_Knowledge Organizational_Knowledge KM Information_Value Human_Resources Finance Community_of_Practice Social_Network_Analysis Knowledge_Utilization Ethnographic_Study Social_Capital Organizations are increasingly providing Communities of Practice with resources to improve the exchange and flow of knowledge and information. However, as with any other significant investment, managers are naturally interested in, and are frequently called upon to justify, the impact that these communities have on individual performance, overall productivity and the bottom line. In this chapter, we present the results of work with thirteen Communities of Practice focusing on how managers can collect community benefits via serious anecdotes and measure the impact that communities have on time use in knowledge work activities and on individual, community and organizational benefits.http://www.bibsonomy.org/bibtex/2022c2fbab2dccc2bd4341a553d8f6574/mstrohmmstrohm2008-04-08T18:00:56+02:00folksonomy networks MUSTREAD SNA <span style="color:#555555;">M. <a href="http://www.bibsonomy.org/author/Latapy">Latapy</a> and C. <a href="http://www.bibsonomy.org/author/Magnien">Magnien</a> and N. <a href="http://www.bibsonomy.org/author/Del Vecchio">Del Vecchio</a> </span><em>Arxiv preprint cond-mat/0611631</em>(<em>2006</em>)Tue Apr 08 18:00:56 CEST 2008Arxiv preprint cond-mat/0611631{Basic Notions for the Analysis of Large Affiliation Networks/Bipartite Graphs}2006folksonomy networks MUSTREAD SNA discusses how to estimate key network affiliation measures (such as average size of events, and average rates of affiliation) when one does not have a complete affiliation network, but only a sample of N and M.http://www.bibsonomy.org/bibtex/241e7e6f3ce88c4d1f6de03ac2c57f1b5/mstrohmmstrohm2008-04-08T16:37:13+02:00SNA networks TOREAD <span style="color:#555555;">J.M. <a href="http://www.bibsonomy.org/author/McPherson">McPherson</a> </span><em>Social Networks</em>(<em>1982</em>)Tue Apr 08 16:37:13 CEST 2008Social Networks225--249{Hypernetwork Sampling: Duality and Differentiation Among Voluntary Organizations}31982SNA networks TOREAD http://www.bibsonomy.org/bibtex/2b213936f7cd7be5e980d2090569b7699/mstrohmmstrohm2008-04-07T19:44:05+02:00networks SNA <span style="color:#555555;">J. <a href="http://www.bibsonomy.org/author/Scripps">Scripps</a> and P.N. <a href="http://www.bibsonomy.org/author/Tan">Tan</a> and A.H. <a href="http://www.bibsonomy.org/author/Esfahanian">Esfahanian</a> </span><em>Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis</em>(<em>2007</em>)Mon Apr 07 19:44:05 CEST 2008Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis26--35{Node roles and community structure in networks}2007networks SNA focuses on bipartite / affiliation networkshttp://www.bibsonomy.org/bibtex/250103469c4e839b6f05a522eaacaa3a8/wnpxrzwnpxrz2008-04-03T16:47:59+02:00network sna social proj:bk analysis <span style="color:#555555;">L.C. <a href="http://www.bibsonomy.org/author/Freeman">Freeman</a> and D.R. <a href="http://www.bibsonomy.org/author/White">White</a> </span><em>Sociological Methodology</em>(<em>1993</em>)Thu Apr 03 16:47:59 CEST 2008Sociological Methodology127--146{Using Galois Lattices to Represent Network Data}231993network sna social proj:bk analysis http://www.bibsonomy.org/bibtex/28debc627ebebb4147af1a3c134420d7e/mstrohmmstrohm2008-03-18T19:08:34+01:00networks SNA MUSTREAD <span style="color:#555555;">S. P. <a href="http://www.bibsonomy.org/author/Borgatti">Borgatti</a> and M. G. <a href="http://www.bibsonomy.org/author/Everett">Everett</a> </span><em>Social Networks</em><em>19(3):243--269</em><em>#aug#1997. </em>Tue Mar 18 19:08:34 CET 2008Social Networks#aug#3243--269Network analysis of 2-mode data191997networks SNA MUSTREAD Network analysis is distinguished from traditional social science by the dyadic nature of the standard data set. Whereas in traditional social science we study monadic attributes of individuals, in network analysis we study dyadic attributes of pairs of individuals. These dyadic attributes (e.g. social relations) may be represented in matrix form by a square 1-mode matrix. In contrast, the data in traditional social science are represented as 2-mode matrices. However, network analysis is not completely divorced from traditional social science, and often has occasion to collect and analyze 2-mode matrices. Furthermore, some of the methods developed in network analysis have uses in analysing non-network data. This paper presents and discusses ways of applying and interpreting traditional network analytic techniques to 2-mode data, as well as developing new techniques. Three areas are covered in detail: displaying 2-mode data as networks, detecting clusters and measuring centrality.focuses on bipartite / affiliation networkshttp://www.bibsonomy.org/bibtex/250103469c4e839b6f05a522eaacaa3a8/mstrohmmstrohm2008-03-18T19:05:00+01:00MUSTREAD SNA networks folksonomy <span style="color:#555555;">L.C. <a href="http://www.bibsonomy.org/author/Freeman">Freeman</a> and D.R. <a href="http://www.bibsonomy.org/author/White">White</a> </span><em>Sociological Methodology</em>(<em>1993</em>)Tue Mar 18 19:05:00 CET 2008Sociological Methodology127--146{Using Galois Lattices to Represent Network Data}231993MUSTREAD SNA networks folksonomy http://www.bibsonomy.org/bibtex/21cb579ea5862acacbf809ef368edd87f/mstrohmmstrohm2008-03-18T16:07:00+01:00SNA SEMINAL networks <span style="color:#555555;">J. <a href="http://www.bibsonomy.org/author/Leskovec">Leskovec</a> and E. <a href="http://www.bibsonomy.org/author/Horvitz">Horvitz</a> </span><em>MSR-TR-2006-186. </em><em>Microsoft Research, </em><em>June2007. </em>Tue Mar 18 16:07:00 CET 2008JuneMSR-TR-2006-186{Worldwide Buzz: Planetary-Scale Views on an Instant-Messaging Network}2007SNA SEMINAL networks http://www.bibsonomy.org/bibtex/2b3853c11f464f13734a2e381414ca1fc/heinzwittenbrinkheinzwittenbrink2008-03-04T08:06:30+01:00Web Agents, Informatik, ,DAT 28 Networks, DAT 614d; Trust, 565d,H.4.3, 612d; WIR Cooperative H.5.3, Supported CSCW,Soziale Agenten, H.5.4,Social Interaktion Vertrauen, via:ThomasPleil, Web, E.1, CSCW,via:ThomasPleil / SNA Semantic Beziehung, (Informatik) J.4, Work, Datenverarbeitung,Computer Agent <span style="color:#555555;">Michael <a href="http://www.bibsonomy.org/author/Galla">Galla</a> </span><em>Technische Universit&#228;t M&#252;nchen, </em>(<em>2004</em>) <em>#Abstract-ENG . </em>Tue Mar 04 08:06:30 CET 2008\#Abstract-ENGSocial Relationship Management in Internet-based Communication and Shared Information SpacesText.PhDThesis2004Web Agents, Informatik, ,DAT 28 Networks, DAT 614d; Trust, 565d,H.4.3, 612d; WIR Cooperative H.5.3, Supported CSCW,Soziale Agenten, H.5.4,Social Interaktion Vertrauen, via:ThomasPleil, Web, E.1, CSCW,via:ThomasPleil / SNA Semantic Beziehung, (Informatik) J.4, Work, Datenverarbeitung,Computer Agent Abstract in English Communication and collaboration based on the internet are important factors in business, research, and everyday life. The term virtualization denotes the phenomenon that more and more aspects of our lives take place online. In today’s markets, companies have to be quick and flexible in order to be successful. One of the strategies to achieve this is the virtualization of organizations, leading to the abolishment of classical spatial and temporal constraints and to a greater flexibility. The dynamic collaboration of small, modular organizational units is the key idea of this strategy. The partnering problem becomes the pivotal point in such organization networks, raising the question of how to assess the trustworthiness of personally unknown potential partners. Similarly, in online auction houses, customers often do not know whether to trust vendors with respect to the quality of the goods offered. Traditionally, such problems are solved by exploring the personal social network and looking for trusted persons who know the person or organization in question. Yet, due to the increasing variety of communication media, it is difficult to keep aware of all people in one’s personal social network. Therefore it is necessary to support the management of social relationships. The goal of this thesis is the development of a general framework for social relationship management. Starting from observations concerning the aforementioned virtualization tendencies, this work examines internet-based communication and shared information spaces with respect to the kinds of social network data that can be extracted from them. Existing approaches to social relationship management are discussed. Such systems, however, concentrate on only one or very few kinds of social relationships and thus only manage special aspects of a user’s social network. Therefore, a general representation of social relationships is needed which allows for the combination of various kinds of relationships and sources of social network data. On the basis of this analysis and the characterization of social relationships in terms of sociology, this work introduces a formal model of social relationships based on semantic web technologies. The main design goals of this formalization are fostering interoperability, independence from proprietary applications, extensibility, and integration of privacy protection. Building upon the formalization of social relationships, a multiagent system for distributed relationship management is developed. Agents act on behalf of one or several persons and exchange relationship information in order to answer queries initiated by their users or by applications. Three query types can be distinguished: - Exploring the social network up to a certain depth - Checking if a relationship chain with certain characteristics from one person to another exists - Retrieving relationship chains with certain characteristics from one user to another With the help of these three query types both the problem of how to get a trusted estimation of another person’s reputation and the problem of how to keep aware of all people in one’s personal social network can be solved. The concepts developed in this work have been prototypically implemented and represent a comprehensive solution of the aforementioned problems of social relationship management in internetbased communication and shared information spaces. Abstract in Deutsch Kommunikation und Kollaboration auf Basis des Internets sind heute wichtige Faktoren in Wirtschaft, Forschung und Privatleben. Der Begriff "Virtualisierung" greift das Phänomen auf, dass mehr und mehr Teile unseres Alltags "online" stattfinden. In heutigen Märkten müssen Unternehmen schnell und flexibel sein, um Erfolg zu haben. Eine der Strategien hierzu ist die Abwendung von klassischen räumlichen und zeitlichen Einschränkungen in Richtung der Virtualisierung von Organisationen und damit in Richtung einer erhöhten Flexibilität. Die dynamische, auftragsbezogene Zusammenarbeit kleiner und modularer organisatorischer Einheiten ist die Schlüsselidee dieser Strategie. Die Partnerfindung wird hierbei zur zentralen Problemstellung und führt zu der Frage, wie die Vertrauenswürdigkeit unbekannter möglicher Partner effektiv und effizient eingeschätzt werden kann. Ähnliche Fragestellungen treten in Online-Auktionshäusern auf, wo Käufer häufig die Vertrauenswürdigkeit der Verkäufer nur schwierig einschätzen können. Traditionell werden solche Probleme mit Hilfe des eigenen sozialen Beziehungsnetzwerks gelöst, indem Personen befragt werden, die bereits Erfahrungen mit dem fraglichen Verkäufer sammeln konnten. Aufgrund der Vielzahl der verwendeten Kommunikationsmedien ist es jedoch zunehmend schwierig, einen Überblick über das eigene soziale Netzwerk zu behalten. Eine Unterstützung hierfür ist notwendig. Das Ziel dieser Arbeit ist die Entwicklung eines allgemeinen Frameworks für soziales Beziehungsmanagement. Ausgehend von den zuvor erwähnten Visualisierungstendenzen untersucht die Arbeit internetbasierte Kommunikation und gemeinsame Informationsräume in Bezug auf Informationen über soziale Beziehungsnetzwerke. Existierende Ansätze hierzu werden untersucht. Existierende Systeme konzentrieren sich jedoch stets auf einen kleinen Ausschnitt der möglichen Aspekte sozialer Beziehungen und liefern daher nur unvollständige Informationen. Daher wird ein allgemeiner Ansatz benötigt, der die Integration von Beziehungsinformationen verschiedenster Arten und aus verschiedensten Quellen erlaubt. Ausgehend von der Analyse sozialer Beziehungen und ihrer Charakterisierung anhand von Begriffen aus dem Fachbereich der Soziologie führt die Arbeit ein formales Modell für soziale Beziehungen ein, das auf Methoden des Semantic Web aufbaut. Die Hauptziele dieser Formalisierung sind Interoperabilität, Unabhängigkeit von speziellen Anwendungen, Erweiterung sowie die Berücksichtigung von Privatheit. Aufbauend auf die Formalisierung von sozialen Beziehungen stellt die Arbeit ein Multiagentensystem für Beziehungsmanagement vor. Agenten agieren im Auftrag von Benutzern und verwalten Beziehungsinformationen oder tauschen Informationen untereinander aus, um Anfragen ihrer Benutzer zu beantworten. Drei wesentliche Arten von Anfragen können hier unterschieden werden: - Erkunden des sozialen Netzwerks bis zu einer bestimmten Tiefe - Prüfen, ob es eine Beziehungskette mit bestimmten Eigenschaften von einer Person zu einer anderen Person gibt - Ermitteln aller solcher Beziehungsketten. Auf Basis dieser drei Anfragearten ist es möglich, die beiden eingangs genannten Probleme zu lösen, namentlich die Einschätzung der Vertrauenswürdigkeit unbekannter Personen sowie die Verbesserung des Überblicks über das eigene soziale Netzwerk. Die Ansätze dieser Arbeit wurden prototypisch implementiert und stellen eine umfassende Lösung für die genannten Probleme bei sozialem Beziehungsmanagement bei internetbasierter Kommunikation und gemeinsamen Informationsräumen dar.Bettina Hoser - Team - Information Services and Electronic Marketshttp://www.bibsonomy.org/bibtex/27f1bcb0e4f71c4619926d8e62f86ae2f/hothohotho2008-02-28T11:54:06+01:00sna diss hoser <span style="color:#555555;">Bettina <a href="http://www.bibsonomy.org/author/Hoser">Hoser</a> </span><em>Universit&#228;tsverlag Karlsruhe, </em>(<em>2005</em>)Thu Feb 28 11:54:06 CET 2008Analysis of Asymmetric Communication Patterns in Computer Mediated Communication Environments2005sna diss hoser