Abstract: Design science is a typical research paradigm within the field of information management and information systems. In recent years, the proportion of design science in information management research has gradually increased. Taking the “Big data-Small data” problem in design science as an example which aims to improve the efficiency of data factor usage, this paper proposes a novel problem of “Big data-Small data” in social networks. Following the design science paradigm, this paper also proposes a framework to solve the problem, i.e., AIRep, an author influence-based representative information extraction framework, and then demonstrates the effectiveness of the extraction results with the data from an internal social networks platform in a Chinese enterprise. Finally, it analyses and discusses the seven guidelines of the design science paradigm based on the “Big data-Small data” research in social networks.

Key words: “Big data-small data” problem, Design science, Information management, Design guidelines, Social network