Seed Selection Strategies in a Sparse Social Network in Rural Zambia: An Empirical ABM Approach
Beatrice Nöldeke, Steven Gronau, Ulrike Grote, Etti Winter
Leibniz University Hannover, Institute for Environmental Economics and World Trade, Germany
Identifying the optimal set of seeds (farmers who obtain information initially) in social networks poses an important question for policy-makers and organisations in developing countries where information is commonly spread through word-of-mouth communication. Widespread provision of adequate information to farmers is particularly important in the context of innovation adoption which has high potential to improve farmers' productivity and adaptation abilities. This paper systematically evaluates different strategies for seed selection with the aim of optimising the seed set to improve knowledge diffusion in a sparse social network in a case study area of rural Zambia. The seed selection strategies include random, hierarchy (village heads), betweenness, closeness, degree, and eigenvector based choice. In addition, the effect of the number of seeds on the diffusion process is investigated. To test for robustness, the study includes the assessment of interaction effects between seed size and seeding strategy. An agent-based model adjusted to a case study area in rural Zambia is applied.
Keywords: Agent-based modelling, information diffusion, seeding, sparse social networks
Contact Address: Beatrice Nöldeke, Leibniz University Hannover, Institute for Environmental Economics and World Trade, Am Königsworther Platz 1, 30167 Hanover, Germany, e-mail: noeldekeiuw.uni-hannover.de