Open AccessThe Social Engagement to Agricultural Issues using Social Network Analysis
Author(s) -
Tanty Yanuar Widiyanti,
Teguh Bharata Adji,
Indriana Hidayah
Publication year - 2021
Publication title -
ijid (international journal on informatics for development)/international journal on informatics for development
Language(s) - English
Resource type - Journals
eISSN - 2549-7448
pISSN - 2252-7834
DOI - 10.14421/ijid.2021.2185
Subject(s) - centrality , betweenness centrality , dissemination , closeness , social network analysis , social network (sociolinguistics) , social media , government (linguistics) , computer science , statistics , world wide web , mathematics , telecommunications , mathematical analysis , linguistics , philosophy
Twitter is one of the micro-blogging social media which emphasizes the speed of communication. In the 4.0 era, the government also promotes the distribution of information through social media to reach the community from various lines. In previous research, Social Network Analysis was used to see the relationship between actors in a work environment, or as a basis for identifying the application of technology adoption in decision making, whereas no one has used SNA to see trends in people's response to agricultural information. This study aims to see the extent to which information about agriculture reaches the community, as well as to see the community's response to take part in agricultural development. This article also shows the actors who took part in disseminating information. Data was taken on November 13 to 20, 2020 from the Drone Emprit Academic, and was taken limited to 3000 nodes. Then, the measurements of the SNA are represented on the values of Degree Centrality, Betweenness Centrality, Closeness Centrality, and Eigenvector Centrality. @AdrianiLaksmi has the highest value in Eigenvector Centrality and Degree Centrality, he has the greatest role in disseminating information and has many followers among other accounts that spread the same information. While the @RamliRizal account ranks the highest in Betweenness Centrality, who has the most frequently referred information, and the highest Closeness Centrality is owned by the @baigmac account because of the fastest to re-tweet the first information.