Dr Swarnakar is trained as environmental sociologist specialised in climate change policy, social network analysis and sustainability transition. He is an administrative board member of an international project group “Climate Change Policy Network” which deals with the climate policy of 20 countries. As an expert of social and discourse network analyst, he is instrumental in policy network data analysis of India, Finland, USA, Brazil and Australia. He has worked with a range of international scholars and published peer-reviewed article in Socius, British Journal of Sociology, Environmental Science and Policy, and Economic and Political Weekly. He has been a visiting scholar at the Department of Environmental Studies, University of San Francisco, USA, the Department of Social Research, University of Helsinki, Finland, and the Department of Urban and Environmental Sociology, Helmholtz Centre for Environmental Research GmbH-UFZ, Germany. He has been awarded prestigious Fulbright-Nehru fellowship to study "Sociocultural dimension of drought management in the era of climate change: Lessons learned from California." He is co-editor of the book Bottom-up Approaches in Governance and Adaptation for Sustainable Development: Case Studies from India and Bangladesh (SAGE Publications, 2017).
Member of Board of Governors of the Research Committee on Environment and Society (RC24) International Socological Association, Member of American Sociological Association, Member of Indian Sociological Association
Environmental Sociology, Climate Change Policy, Social Media, Social Networks, Sustainability Transition
Environmental Sociology, Introduction to Sociology, Sociology and Social Problems of India, Research Methodology
Kumar, A, Swarnakar, P, Jaiswal, K & Kurele, R 2020, 'SMIR model for controlling the spread of information in social networking sites', PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, vol. 540.View/Download from: Publisher's site
Kukkonen, A, Yla-Anttila, T, Swarnakar, P, Broadbent, J, Lahsen, M & Stoddart, MCJ 2018, 'International organizations, advocacy coalitions, and domestication of global norms: Debates on climate change in Canada, the US, Brazil, and India', ENVIRONMENTAL SCIENCE & POLICY, vol. 81, pp. 54-62.View/Download from: Publisher's site
Swarnakar, P, Kumar, A & Tyagi, H 2017, 'Network dynamics in friend recommendation: A study of Indian engineering students', International Journal of Information Technology and Management, vol. 16, no. 3, pp. 287-300.View/Download from: Publisher's site
Copyright © 2017 Inderscience Enterprises Ltd. Social networks are the frequently used service which over the past few years, have grown by leaps and bounds. In this study, a survey of engineering students has been conducted to find out the most relevant socio-demographic and webographic factors that are considered by users while sending/accepting friend requests. An extensive survey has been conducted and the responses were used to determine the influence of various factors in friend request attributes. Based on the collected responses, logistic regression and artificial neural network models have been developed for predicting the users' friend request attributes. A comparative performance analysis of these models to predict the friend request attributes has also been done. The results indicate that neural network model outperformed the logistic regression model when data are nonlinear. The study also shows that among all the factors, users' gender, photographs, hometown, age, and shared interests are the most significant factors.
Yla-Anttila, T & Swarnakar, P 2017, 'Crowding-in: how Indian civil society organizations began mobilizing around climate change', BRITISH JOURNAL OF SOCIOLOGY, vol. 68, no. 2, pp. 273-292.View/Download from: Publisher's site
Swarnakar, P, Kumar, A & Wadhwa, M 2016, 'Investigating preferred relationship through fuzzy sets in social networking sites', International Journal of Web Based Communities, vol. 12, no. 2, pp. 165-179.View/Download from: Publisher's site
© Copyright 2016 Inderscience Enterprises Ltd. The aim of this paper is to identify the strength of socio-demographic factors that motivate a user to send friend request on social networks. The study is supported by a primary survey that identifies five factors of the user's namely, age, sex, mutual friends, school and relationship status which are important in sending friend request. Fuzzy numbers are used to represent the identified factors because they allow expert opinions, uncertainty and impreciseness to be incorporated into the model. A multiple input, single output (MISO) model has been developed using Mamdani fuzzy inference system (FIS) and sensitivity analysis has been done. The results obtained show how the fuzzy logic approach translates vague, ambiguous, qualitative and imprecise information into numerical terms, which helps to identify the most informative contents while sending friend request. The paper also integrates primary survey and expert judgement to gain a deeper insight about the social behaviour.
Ylä-Anttila, T, Swarnakar, P, Javed, S & Oivo, K 2015, 'How to avoid seeing like a state: Learning from CSOs', Economic and Political Weekly, vol. 50, no. 17, pp. 14-16.
If a government's policies are planned from a bird's-eye view with insuffi cient knowledge of local conditions and livelihoods, they can go wrong. Civil society organisations on their part have the capability to act as a link between locals and decision-makers. CSOs are worth listening to because they might just have seen something that the state cannot see.