Socio-Sentic framework for sustainable agricultural governance

Abstract

Livelihood security plays a critical role in strengthening the socio- economic situation of a country. Agriculture is one such sector which is expected to provide a complete array of economic, social, and environmental services. Good governance and management of allied policies at all levels is favourable for long-term sustainability of agricultural sector. The accountability of government is a direct measure of its social responsibility and sustainability. Social media as a powerful online platform reinforces hype and provides opportunities to extract and analyze public opinion about various governmental schemes and policies including the ones related to agriculture. The e-participation platforms such as Twitter offer unparallel means to intelligently gauge the consensus and orientation of people towards an agricultural policy. Motivated by this, the work presented in this research, proffers a Socio-Sentic framework for sustainable agricultural governance which probes the sentiment polarity of user-content on Twitter pertaining to government policies, specifically agricultural policies. In this intelligent analytic framework, supervised machine learning algorithms have been implemented and compared using tweets on an Indian Agricultural Policy launched in 2016, ‘Pradhan Mantri Fasal Bima Yojana’ (PMFBY). The preliminary results indicate that the adoption of the proposed framework for soliciting and probing citizen feedback for government policy evaluation can lead to a sustainable agricultural development.