This section discusses the use of Action Design Research methodology in particu- lar. Furthermore, it reflects on the lack of comparative studies between Social Set Analysis and Social Network Analysis, the data collection pipeline of the Social Set Visualizer, and the application of Social Set Analysis to non-Facebook datasets.
6.1.1 Use of Action Design Research Methodology
The work in this PhD project is grounded in Action Design Research methodology which relies on an iterative research process. Thus, this thesis used the initial for- mulation of the research problems as a starting point. Thereby, a particular focus was set on the current challenges in Big Data Analytics which were identified by the National Academy of Sciences [National Research Council et al. 2013]. This step was accompanied by the identification stage of the research questions concerning Visual Analytics of Big Social Data and the application of the Social Set Analysis approach to Big Social Data Analytics. Subsequently, during the building, intervention, and evaluation (BIE) stage of Action Design Research, three versions of the Social Set Visualizer IT artifact have been designed and implemented. These versions have been presented in Publication I [Vatrapu et al. 2016], Publication II [Fleschet al. 2015a], and Publication III [Flesch et al. 2016] of this dissertation. Furthermore, the novel software tools’ capabilities to generate insights were evaluated through various de- scriptive and predictive case studies.
The IT-dominant BIE stage of Action Design Research relies on the researchers to distribute alpha and beta versions of the IT artifact to practitioners and end- users. In this PhD project, the alpha version was provided to fellow academics who were not part of the development of the software tool. Furthermore, the beta version was given to university students to generate insights from Big Social Data in their course projects. It has to be stated that this obsersation does not reflect the software industry, in which “end-user” demographics rarely consist of a majority of highly- educated students. Hence, a slight bias might have been introduced during the case
84 Chapter 6. Discussion study evaluation of the Social Set Visualizer, as Action Design Research methodology was utilized with academic staff and students instead of industry practitioners and real-world end users.
6.1.2 Social Set Analysis vs. Social Network Analysis Studies
In this thesis, a brief qualitative comparison between Social Set Analysis and Social Network Analysis is presented. However, it can be argued that no exhaustive com- parative study between Social Set Analysis and the historically dominant approach of Social Network Analysis has been conducted using the Social Set Visualizer soft- ware tool. There are several underlying reasons for the presentation of a qualitative comparative evaluation. First, a comprehensive reasoning why Social Set Analysis complements Social Network Analysis and why it is a worthwile undertaking to invest valuable research time into Social Set Analysis is given. This line of reasoning has been argued over various publications to great extent, includingPublication I[Vatrapu et al. 2016] at the beginning of this dissertation. Second, the case studies based on the Social Set Analysis methodology, which were performed during this PhD project, resulted in a variety of novel research findings that needed to be documented and published. Due to this observation, publishing of novel research findings was pri- oritized over implementing replication studies of Social Network Analysis findings. Still, a backlog of ready-to-publish research findings that were gathered by means of Social Set Analysis has been steadily building up over the past three years.
6.1.3 Integrated Data Collection
The methodology of data collection utilized in this PhD project is deeply integrated into the Social Set Visualizer. This integration has been introduced in the third ver- sion of the tool, which is presented in Publication IV [Fleschet al. 2017], whereas previous versions relied on an external source of data such as SODATO, as presented in section 2.4.2. In combination with the Visual Analytics functionality, a large, con- tinuous stretch of the Big Data Value Chain was directly implemented in the latest version of the Social Set Visualizer software tool. This results in a very streamlined acquisition and analysis of Facebook data with tangible benefits for the insight gen- eration from Big Social Data. At the same time, this specialization on the integrated collection of Facebook data depicts a limitation. A data collection functionality for non-Facebook data has not been implemented in the Social Set Visualizer due to lack of API access to other leading social networks such as Instagram.
6.1.4 Social Set Analysis of non-Facebook Datasets
At the beginning of this dissertation, it was shown that this PhD project contributes a significant amount of research on large-scale Facebook datasets to the state of the art in Visual Analytics of Big Social Data. In my presented publications, the novel set-based approach to Big Social Data Analytics, Social Set Analysis, was utilized. This shows a methodological limitation of the work presented in this thesis, as all
6.2. Reflections on the Visualization of Large-scale Sets 85