Social network analysis of spreading and exchanging information on Twitter: the case of an agricultural research and education centre in Mexico
Open Access
- 20 April 2021
- journal article
- research article
- Published by Taylor & Francis Ltd in The Journal of Agricultural Education and Extension
- Vol. 28 (1), 115-136
- https://doi.org/10.1080/1389224x.2021.1915829
Abstract
Purpose – This paper aims to contribute to deepening insights on social media in agricultural research by presenting a case study on how a research and education centre in Mexico connected, communicated, and interacted in a research and education community on Twitter. Design/methodology/approach – By using a Social Network Analysis (SNA) approach, 1585 tweets were analysed. The data was gathered using NodeXL. Afterwards, SNA was performed through the igraph R package. Findings – The dynamic of virtual interaction around an agricultural research and education centre shows that different roles are needed to connect and foster the interaction on Twitter, as well as to spread information broader. While some accounts are functioning as creators of information, others act as consumers and diffusers of it, and a few more accounts play both roles. Practical Implications – To increase the size and strengthen the interaction of a network on Twitter, it is advisable to have the support of other accounts and to promote its use among potential users. This requires capabilities to develop a social media strategy and pro-actively engage new followers. Theoretical Implications – Through a SNA approach, it is possible to understand better the functions of weak and strong ties in virtual settings, i.e. the former to extend the network, and the latter to strengthen it. These ties can enhance information dissemination and enable exchanges on social media. Originality/value – This paper applies SNA as a theoretical and methodological framework to demonstrate that the interactions among users are different when a whole network is analysed, and when it is divided into the mentions and retweets networks. By doing this, hidden patterns are revealed.Keywords
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