Social Networks like Facebook, Twitter, YouTube and WhatsApp are now becoming very popular tools that are used for sharing the latest and important farming based information in different part of India. These tools are now widely used by Agricultural Extension and Advisory services to interact with the farmers for exchanging agricultural related information in India. The most influential farmers in a network can disseminate the information to the less central farmers of the network. The extension functionaries that promote the agricultural innovation will share the information with the most central members which in turn will share it with maximum number of the members of a social network. Social Network Analysis (SNA) acts as an efficient analytical tool that helps us to understand the relationship between farmer stakeholders and the importance of a farmer's position in the entire network. In this paper, a structural analysis of the Social Network is performed over two datasets, namely, Facebook-like dataset and Twitter Lists dataset. Here, we have studied the importance of individual nodes in the network through various centrality measures. SNA properties like centralities are used to represent the most central nodes that can act as a good influence spreader in the network. In this paper, initially the k-core decomposition method is used to find a set of influential nodes among all the nodes in the network. It is done to reduce the computational time. Our simulation shows that the nodes with higher Page Rank centrality can activate more members in a network as compared to other centrality measures. For Information diffusion, we have used Linear Threshold (LT) Model to understand the influence spread of the central farmers in the network.
27 pages., The provision of information through mobile phone-enabled agricultural information services (m-Agri services) has the potential to revolutionise agriculture and significantly improve smallholder farmers’ livelihoods in Africa. Globally, the benefits of m-Agri services include facilitating farmers’ access to financial services and sourcing agricultural information about input use, practices, and market prices. There are very few published literature sources that focus on the potential benefits of m-Agri services in Africa and none of which explore their sustainability. This study, therefore, explores the evolution, provision, and sustainability of these m-Agri services in Africa. An overview of the current landscape of m-Agri services in Africa is provided and this illustrates how varied these services are in design, content, and quality. Key findings from the exploratory literature review reveal that services are highly likely to fail to achieve their intended purpose or be abandoned when implementers ignore the literacy, skills, culture, and demands of the target users. This study recommends that, to enhance the sustainability of m-Agri services, the implementers need to design the services with the users involved, carefully analyse, and understand the target environment, and design for scale and a long-term purpose. While privacy and security of users need to be ensured, the reuse or improvement of existing initiatives should be explored, and projects need to be data-driven and maintained as open source. Thus, the study concludes that policymakers can support the long-term benefit of m-Agri services by ensuring favourable policies for both users and implementers.
