Social Academic Analytics (SAA) is proposed as a new research specialty. With its focus on the four key areas, SAA highlights the need for a systematic way of exploring relational data within knowledge networks and can be considered as a strategic instrument in educational data management.
SAA provides the concepts for building a clear understanding of the activities of entities, patterns of collaboration, organizational structures, and structural cohesion over time by implementation of dynamic modeling of (social) evolution for monitoring and preventing of unwanted outcomes. For future research we suggest the evaluation of SAA as concept in applied research. Answering the question »Who (or what) is connected to whom (or what) by which channels in which time with what effects?« is one of the major research problems that SAA can address. Applied studies of the spectrum of dynamics, competencies, capacities, requirements, and applicability are necessary for continuous improvements of SAA.
We propose that software programmers in knowledge organizations should develop integrated (dynamic) techniques to handle relational data within a macro perspective, and combine SNA, DNA, SSNA, and VA as comprehensive applicable management software tool.