Details
Originalsprache | Englisch |
---|---|
Aufsatznummer | 9 |
Seiten (von - bis) | 1-24 |
Seitenumfang | 24 |
Fachzeitschrift | Journal of Artificial Societies and Social Simulation |
Jahrgang | 23 |
Ausgabenummer | 4 |
Publikationsstatus | Veröffentlicht - 31 Okt. 2020 |
Abstract
The successful adoption of innovations depends on the provision of adequate information to farmers. In rural areas of developing countries, farmers usually rely on their social networks as an information source. Hence, policy-makers and program-implementers can benefit from social diffusion processes to effectively dis-seminate information. This study aims to identify the set of farmers who initially obtain information (‘seeds’) that optimises diffusion through the network. It systematically evaluates different criteria for seed selection, number of seeds, and their interaction effects. An empirical Agent-Based Model adjusted to a case study in rural Zambia was applied to predict diffusion outcomes for varying seed sets ex ante. Simulations revealed that informing farmers with the most connections leads to highest diffusion speed and reach. Also targeting village heads and farmers with high betweenness centrality, who function as bridges connecting different parts of the network, enhances diffusion. An increased number of seeds improves reach, but the marginal effects of additional seeds decline. Interdependencies between seed set size and selection criteria highlight the importance of considering both seed selection criteria and seed set size for optimising seeding strategies to enhance information diffusion.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Informatik (sonstige)
- Sozialwissenschaften (insg.)
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in: Journal of Artificial Societies and Social Simulation, Jahrgang 23, Nr. 4, 9, 31.10.2020, S. 1-24.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Seed selection strategies for information diffusion in social networks
T2 - An agent-based model applied to rural zambia
AU - Nöldeke, Beatrice
AU - Winter, Etti
AU - Grote, Ulrike
N1 - Funding information: We thank the community of Mantapala for their participation and continuous cooperation. We also thank the Zambian local Ministry of Agriculture for their support in the organization of the research activities. This work was supported by the Federal Office for Agriculture and Food (BLE) and funded by the Federal Ministry of Food and Agriculture (BMEL) under grant 2813FSNU11. The model is adjusted to a study area called Mantapala, which is located within the Congo Basin in northern Luapula Province of Zambia as illustrated in Figure 1. The study area was selected within the framework of the project Food Security in Rural Zambia (FoSeZa), funded by the German Federal Ministry of Food and Agriculture (BMEL). According to stakeholder discussions and results of a pilot survey, the region shows typical features of a rural village in a developing country such as a remote location, lack of infrastructure development (roads, electricity, market integration, etc.), pronounced malnutrition, and food insecurity (Hampwaye et al. 2014; Central Statistical Office Zambia 2016; Gronau et al. 2018). Given the distinct impoverishment combined with high food insecurity and dependence on farming, research regarding the spread of agricultural innovations can contribute to improving local livelihoods (Hampwaye et al. 2014; Central Statistical Office Zambia 2016, 2018; Gronau et al. 2018).
PY - 2020/10/31
Y1 - 2020/10/31
N2 - The successful adoption of innovations depends on the provision of adequate information to farmers. In rural areas of developing countries, farmers usually rely on their social networks as an information source. Hence, policy-makers and program-implementers can benefit from social diffusion processes to effectively dis-seminate information. This study aims to identify the set of farmers who initially obtain information (‘seeds’) that optimises diffusion through the network. It systematically evaluates different criteria for seed selection, number of seeds, and their interaction effects. An empirical Agent-Based Model adjusted to a case study in rural Zambia was applied to predict diffusion outcomes for varying seed sets ex ante. Simulations revealed that informing farmers with the most connections leads to highest diffusion speed and reach. Also targeting village heads and farmers with high betweenness centrality, who function as bridges connecting different parts of the network, enhances diffusion. An increased number of seeds improves reach, but the marginal effects of additional seeds decline. Interdependencies between seed set size and selection criteria highlight the importance of considering both seed selection criteria and seed set size for optimising seeding strategies to enhance information diffusion.
AB - The successful adoption of innovations depends on the provision of adequate information to farmers. In rural areas of developing countries, farmers usually rely on their social networks as an information source. Hence, policy-makers and program-implementers can benefit from social diffusion processes to effectively dis-seminate information. This study aims to identify the set of farmers who initially obtain information (‘seeds’) that optimises diffusion through the network. It systematically evaluates different criteria for seed selection, number of seeds, and their interaction effects. An empirical Agent-Based Model adjusted to a case study in rural Zambia was applied to predict diffusion outcomes for varying seed sets ex ante. Simulations revealed that informing farmers with the most connections leads to highest diffusion speed and reach. Also targeting village heads and farmers with high betweenness centrality, who function as bridges connecting different parts of the network, enhances diffusion. An increased number of seeds improves reach, but the marginal effects of additional seeds decline. Interdependencies between seed set size and selection criteria highlight the importance of considering both seed selection criteria and seed set size for optimising seeding strategies to enhance information diffusion.
KW - Agent-Based Modelling
KW - Information Diffusion
KW - Seeding
KW - Social Networks
KW - Zambia
UR - http://www.scopus.com/inward/record.url?scp=85094861369&partnerID=8YFLogxK
U2 - 10.18564/jasss.4429
DO - 10.18564/jasss.4429
M3 - Article
AN - SCOPUS:85094861369
VL - 23
SP - 1
EP - 24
JO - Journal of Artificial Societies and Social Simulation
JF - Journal of Artificial Societies and Social Simulation
SN - 1460-7425
IS - 4
M1 - 9
ER -