Social network analysis approach to identify agricultural key communicators

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dc.contributor.authorYamini, T.en_US
dc.contributor.authorVenkatesan, P.en_US
dc.contributor.authorJyothi, V.en_US
dc.contributor.authorDevy, M.R.en_US
dc.contributor.authorRao, V.S.en_US
dc.contributor.authorSuseela, K.en_US
dc.date.accessioned2025-05-12T10:14:26Z
dc.date.available2025-05-12T10:14:26Z
dc.date.issued2024-12
dc.description.abstractAim: This paper employed Social Network Analysis approach to visualize and calculate different social network metrics. It identifies key communicators who play pivotal roles in information flow. Methodology: Research was conducted at Jammulapalem and Perali villages of Bapatla district, Andhra Pradesh, India, during 2022-23 using an exploratory research design. A total of 120 farmers Eigen vector were selected using simple random technique, and data was collected using a well-developed interview schedule. Network metrics such as Degree centrality, betweenness centrality, and eigen vector centrality were computed to evaluate the network structure using R software (version 4.3.1). R packages, namely igraph, statnet and network D3, were used for network creation, analysis and visualization to identify the influential nodes. Results: The study revealed a complex web of relationships among various stakeholders within the agricultural network through a network graph, identifying key communicators with the highest Degree centrality. Interpretation: The focal points identified through Social Network Analysis represent a specific demographic and socio-economic group, typically aged between 35 and 55, primarily medium-scale farmers,with landholdings spanning 10 to 25 acres and high annual income, with educational backgrounds ranging from high school to pre-university college, and wield significant influence within their local communities. They require sensitization, training, practical demonstrations, and personalized support to effectively disseminate agricultural information.en_US
dc.identifier.affiliationsDepartment of Agricultural Extension Education, Agricultural College, Bapatla -522 101, Indiaen_US
dc.identifier.affiliationsExtension Systems Management, ICAR-NAARM, Hyderabad -500 030, Indiaen_US
dc.identifier.affiliationsDepartment of Agricultural Extension Education, Agricultural College, Bapatla -522 101, Indiaen_US
dc.identifier.affiliationsDepartment of Agricultural Extension Education, Agricultural College, Bapatla -522 101, Indiaen_US
dc.identifier.affiliationsDepartment of Statistics and Computer Applications, Agricultural College, Bapatla -522 101, Indiaen_US
dc.identifier.affiliationsDepartment of Agricultural Economics, Agricultural College, Bapatla-522 101, Indiaen_US
dc.identifier.citationYamini T., Venkatesan P., Jyothi V., Devy M.R., Rao V.S., Suseela K. . Social network analysis approach to identify agricultural key communicators. Journal of Environmental Biology. 2024 Dec; 45(6): 788-797en_US
dc.identifier.issn0254-8704
dc.identifier.issn2394-0379
dc.identifier.placeIndiaen_US
dc.identifier.urihttps://imsear.searo.who.int/handle/123456789/247539
dc.languageenen_US
dc.publisherTriveni Enterprisesen_US
dc.relation.issuenumber6en_US
dc.relation.volume45en_US
dc.source.urihttps://doi.org/10.22438/jeb/45/6/MRN-5366en_US
dc.subjectAgricultural Information System Networken_US
dc.subjectCentrality measuresen_US
dc.subjectInformation Sourcesen_US
dc.subjectKey Communicatorsen_US
dc.subjectNetwork visualizationen_US
dc.subjectSocial Network Analysisen_US
dc.titleSocial network analysis approach to identify agricultural key communicatorsen_US
dc.typeJournal Articleen_US
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