Information networks, especially citation networks, have many proven and potential applications in scientometrics. Identification of productivity of authors and journals is one of the prime concern of analysts. While there are many indices to measure the productivity of author or journal, there is no known index to determine productivity with respect to a particular research context. A network scientometric approach is devised to address the identification of contextual productivity. Work-author and Work-journal affiliations modelled as 2 mode networks provide effective means to assess the productivity of authors and journals in a particular research context. In this work, weighted 2 mode networks are created for the analysis of affiliations networks such that weights reflect some citation characteristics of the works in their original citation network. A set of network indices are proposed for the assessment of contextual importance of authors and journals which are illustrated in the case study of Biotechnology for Engineering. Online databases and digital libraries can use these indices to gather insights about most productive authors and journals, along with the search results.
['Hiran H. Lathabai', 'Thara Prabhakaran', 'Manoj Changat']
Contextual productivity assessment of authors and journals: a network scientometric approach