Integrated Representation and Visualisation of the Dynamics in Computer-mediated Social Networks

Abstract

In this paper we will demonstrate the potential of processing and visualising the dynamics of computermediated communities by means of Social Network Analysis. According to the fact that computer-mediated community systems are manifested also as structured data, we use data structures like e-mail, discussion boards, and bibliography sources for an automatic transformation into social network data formats. Currently our developed converter DMD (Data Multiplexer Demultiplexer) supports GraphML, UCINET, and Pajek formats besides our own data formats which are used for real-time analysis of CSCL (Computer Supported Collaborative Learning) activities. In the case of communication data our converters utilize conversation graphs reflecting aspects of speech act and conversational theory to produce directed graphs in the cases where one-mode person networks are desired.The paper will demonstrate a 3-dimensional visualisation of an author community based on Bibtex bibliography data converted into GraphML. Based on this dataset we visualise publications network with a tool called Weaver, which is developed in our research group. According to Lothar Krempel's algorithm, Weaver uses the first two dimensions to embed the network structure within a common solution space. The third dimension is used for representing the time axis and thus the dynamics of co-authorship relations.Concluding we aim to discuss potential issues and problems of our approach and the possibilities especially concerning the appropriate visualisation and segmentation of long term communications, such as mailing lists.

Using Three Social Network Analysis Approaches to Understand Computer-Supported Collaborative Learning

“…Using Malzahn et al's (2005) algorithm, Harrer et al (2007) demonstrated additional links of interests between two teams in a scientific community mediated by the knowledge maps. Harrer et al (2009) further proposed a schema for multi-mode network transformations and presented a multi-mode network visualization to show temporal changes. In summary, since CSCL usually involves diverse types of entities and relations can develop in various ways, it is necessary to further use multi-mode network analyses to capture relations between entities and the mediating effects (Cela et al, 2015;Dado & Bodemer, 2017;Ouyang & Scharber, 2017).…”

“…(2007) demonstrated additional links of interests between two teams in a scientific community mediated by the knowledge maps. Harrer et al. (2009) further proposed a schema for multi-mode network transformations and presented a multi-mode network visualization to show temporal changes.…”

Using big data techniques for measuring productive friction in mass collaboration online environments

“…For the analysis, the link structures of the Wikipedia article on schizophrenia and related articles that represented various explanatory approaches (social, biological, and psychoanalytical) were analyzed in a series of six annual cross-sectional snapshots for the years 2003-2008. The Weaver software (Harrer et al 2007) was then used to calculate SNA traits, such as centrality and density, for all of the Wikipedia pages that were linked at that time to these articles. Furthermore, SNA also allowed for the calculation of scores of the individual contributors with regard to the closeness or distance of their linking activities to the nodes that represented different views on the causes of schizophrenia.…”

How students emerge as learning leaders in small group online discussions

“…In the context of collaborative online discussions, some students learn by actively evaluating other students' work, providing constructive commentaries and exchanging meaningful resources; other students learn by passive engagement, as well as viewing other students' posts and attached materials (Kim, Yoon, Jo, & Branch, 2018;Wise & Hsiao, 2019). Different levels of students' engagement in the online discourses enable some students to play distinct roles in the collaborative learning community (Harrer, Zeini, & Ziebarth, 2009;Kelly, Davis, Nelson, & Mendoza, 2008;Xie et al, 2018). Given that a discussion forum is a social space, a learning leader can be any student who exerts substantial influence on his or her peers during critical conversations that occur in the discussion forum.…”