Climate change is widely recognized to be a global threat to natural systems, human populations, and economies. India is facing the challenges of sustaining its rapid agricultural growth while dealing with the global threat of climate change. Faced with these threats and challenges there are two major responses for policy intervention in agriculture. The first strategy is to mitigate/reduce the rate and magnitude of climate change itself through reducing the emissions of human causes of climate change, for example, mitigation of greenhouse gases, prevention of soil erosion etc. The second option is to promote adaptation to climate change to minimize the impacts and take advantage of new opportunities and new technologies. The pattern of flow of information through social networks and the factors that facilitate or impede the flow and utilization of such information are among important areas that need to be studied in technology adoption of climate smart technologies in adaptation and mitigation to climate change context. The derivatives of Social Network Analysis (SNA) revealed that Arkaraipatti village had an equal average in-degree and out-degree of 3.619 and similarly, Attur village had an equal average in-degree and out-degree of 2.286. In the social networks of Appipatti and Odaipatti villages of Chinnamanur block, it was found that degree centrality of Appipati village had an equal average in-degree and out-degree of 1.909 and similarly, Odaipatti village had an equal average in-degree and out-degree of 1.571. There was no strong Tie in both the Blocks. Attur block was having more Density (0.16) as compared to Chinnamanur block. With Geodesic Distance of 3.119, Chinnamanur block had advantage to pass information faster. Since, Arkaraipatti and Odaipatti villages augured well in information sharing on mitigation and adaptation of climate change in agriculture as compared to Attur and Appipatti villages.

Keyword: Social network analysis (SNA); In- degree and out -degree; Density; Tie and geodesic distance;