Mapping the communication of agricultural knowledge, an application of social network analysis

Abstract

Scientific knowledge communication is a fundamental part of the scientific progress and vital for modern society. Thus, scientific conferences and congresses are crucial spaces for these processes of communication. This research aims to analyse the communication of scientific works at an agricultural congress, so as to add knowledge to the literature in three streams: data use, methodological application, and empirical evidence. To do this, we analysed 316 presentation titles done over five years. We used two methodological approaches: data mining and social network analysis (SNA). The results show that in the 316 titles, 1, 093 different terms have been used, following a power-law distribution. Through a bigrams network, it was found that these terms are linked by 1, 847 directed ties. Moreover, with SNA, the most important words were identified based on different indicators. It is concluded that the existing information in the files of scientific congresses is rich in content and could be useful for finding knowledge gaps. Furthermore, the used approaches complement each other. This paper provides technical and empirical evidence about the network mining field.