The visualization and analysis of dynamic networks have become increasingly important in several fields, for instance sociology or economics. The dynamic and multi-relational nature of this data poses the challenge of understanding both its topological structure and how it changes over time. In this paper we propose a visual analytics approach for analyzing dynamic networks that integrates: a dynamic layout with user-controlled trade-off between stability and consistency; three temporal views based on different combinations of node-link diagrams (layer superimposition, layer juxtaposition, and two-and-a-half-dimensional view); the visualization of social network analysis metrics; and specific interaction techniques for tracking node trajectories and node connectivity over time. This integration of visual, interactive, and automatic methods supports the multifaceted analysis of dynamically changing networks.
There are currently over 175 million Twitter accounts worldwide, making Twitter one of the most popular and most observed Social Media platform. But Twitter is not so much a social network where the exchange of personal information is facilitated – in fact, recent surveys state that it’s not very social at all with a large amount of inactive accounts and a low motivation of engaging in dialogues . Twitter has rather evolved into a pool of constantly updating information streams consisting of links, short status updates, and eyewitness news. Among the millions of users, a small percentage is what is called the group of influencers or alpha users. They have a large, active audience that consumes and multiplies the content published by the influencer. Thus, an influencer’s content – whether it is plain text or links – is distributed in a number of micro-networks and receives attention from a large amount of users even though they might not even be direct followers of the influencer. The further the content is spread, the further the influence of the user reaches.
There are various tools that enable performance measurement on Social Media. Some only sum up numbers such as the amount of followers or mentions gained on Twitter; others interpret the numbers and rate the performance using a specific algorithm. An example for the latter is Klout, a popular service that will be looked at more closely, focusing on the question of how Klout calculates its scores which serve as a means of measuring success of Twitter usage.
The research purpose of this paper is to determine a grounded approach for measuring social networking potential of individual Twitter users
Web 2.0 platforms such as media sharing and social network sites (SNS) concern people in everyday life to a great extent. People are enabled to reach out to various media and up to now, it is nearly impossible to use digital identities ex ante or to recreate users’ identities ex post across different platforms. In this paper, we explore important methodologies in Web 2.0 such as cross-media analysis and social pattern based analysis based on a survey in this area, aiming at cross-platform information diffusion across social network sites. Open issues are discussed to explore the challenges and solutions in this new research area.
The innovation process is a rhythm of search and selection, exploration and exploitation, cycles of perspectives encountering which allow people to analyze problems from new points of view. In order to enable innovation, a lot of instruments have been developed connecting heterogeneous individuals thinking (e.g. social networks, web portals, wiki systems, organizational yellow-pages, etc.). In this paper we focus on web portals, and how these tools assist the users connections and the innovation processes among them. In particular, we analyze some services implemented in the Innovation Portal of the Brazilian Ministry of Science and Technology geared to stimulating the establishment of strategic partnerships and cooperation projects involving national firms and science institutions. These services are mainly based on social network analysis in order to manage connections (i.e. coordination) and innovation processes among users.
Digital media are used to facilitate social structures thus building digital social networks. Disturbances in such networks occur on different levels (egocentric level, subgroup level, network) and have to be analyzed in the multidimensional context of reference disciplines like sociology and knowledge management. This paper presents a first repository of disturbance patterns for the analysis of digital social networks. Based on the Actor-Network Theory and the Social Network Analysis, new socio-theoretical models for handling complex media settings were developed. On these models a pattern language is defined to describe multidimensional disturbance patterns and to store them in a newly developed pattern repository. The core of the pattern language is the formal expression language for pattern (FELP) which used to specify the structural and the content-specific properties of digital social networks. Results can be visualized with open source graph visualization software. To evaluate the approach a case study has been performed in a repository containing 118 mailing lists and 17.359 individuals. Patterns like troll, spammer and burst have been applied successfully.
Various studies focus on general networks within and between organizations, but strongly focused studies on knowledge sharing through social networks and communities within specific domains that are of critical relevance to the R&D organization are hard to find. Therefore, the argument presented here is explored through an empirical case study on inter-organizational knowledge community building between different research institutes of the Fraunhofer-Gesellschaft, a large German organization for contract research in all fields of the applied engineering sciences. Expert knowledge communication and networking processes are evaluated by a multi-level approach. Institutionalization of knowledge transfer is studied with regard to the development of the informal contacts between the community members and the inter-organizational linkages on an aggregated level. The main focus is put on the relationships of knowledge exchange between the formal organizational boundaries and the informal interorganizational network structures. Finally, this case study aims at further supporting the adaptation of methods from social network analysis for purposes of organization and management practice.
In many organisations, conservation of specialised expertise is picked out as a central theme only after experienced members have already left. The paper presents the SELaKT method, a method for Sustainable Expert Localisation and Knowledge Transfer based on social network analysis (SNA). It has been developed during a project co-operation between the Department of Information Science at the Institute for Media and Communication Studies, Free University Berlin, and the Fraunhofer Institute for Production Systems and Design Technology IPK, Berlin. The SELaKT method uses recent insights into network analysis and pragmatically adapts SNA to suit organisational practice. Thus it provides a strategic tool to localise experts, to identify knowledge communities and to analyse the structure of knowledge flows within and between organisations. The SELaKT method shows its advances and increasing relevance for practical use by integration of specific organisational conditions and requirements into the process of analysis.
Knowledge audit lays a concrete foundation for any knowledge management programs. The central topic of this paper is to integrate various knowledge audit related techniques into pre-audit preparation, in-audit process and post-audit analysis in a systematic manner. Culture assessment, in the form of surveys and radar charts, along with orientation program make up the pre-audit preparation. Structured interviews are carried out to capture process-critical knowledge. Knowledge inventory, knowledge maps and knowledge flow analysis compose of post-audit analysis. Knowledge inventory is then built for stocktaking knowledge assets and thus revealing the key knowledge assets by measuring them against four performance criteria. Knowledge mapping together with social network analysis are to show the knowledge exchange path and make the key knowledge suppliers and customers visible. They are then being further applied into knowledge flow analysis, which serves to reveal the strength and weakness of the current knowledge flow. A case study of applying the designed instruments in the Engineering Division of the Hong Kong Dragon Airlines Limited and the related analysis are also present in this paper.