Technology Diffusion in Social Networks

2009 ◽  
pp. 35-36
Author(s):  
Nicole Immorlica
Keyword(s):  
Social Networks ◽  
Technology Diffusion

scholarly journals Germs, Social Networks and Growth

2021 ◽  
Author(s):  
Alessandra Fogli ◽  
Laura Veldkamp
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Analysis ◽  
Technology Diffusion ◽  
Income Country ◽  
Social Connections ◽  
Rate Of Growth ◽  
High Diffusion ◽  
Analysis Tools ◽  
Diffusion Networks

Abstract Does the pattern of social connections between individuals matter for macroeconomic outcomes? If so, where do differences in these patterns come from and how large are their effects? Using network analysis tools, we explore how different social network structures affect technology diffusion and thereby a country’s rate of growth. The correlation between high-diffusion networks and income is strongly positive. But when we use a model to isolate the effect of a change in social networks on growth, the effect can be positive, negative, or zero. The reason is that networks diffuse both ideas and disease. Low-diffusion networks have evolved in countries where disease is prevalent because limited connectivity protects residents from epidemics. But a low-diffusion network in a low-disease environment compromises the diffusion of good ideas. In general, social networks have evolved to fit their economic and epidemiological environment. Trying to change networks in one country to mimic those in a higher-income country may well be counterproductive.

scholarly journals Caste, Social Networks and Variety Adoption

2020 ◽  
Vol 15 (2) ◽  
pp. 155-183
Author(s):  
Ishika Gupta ◽  
Prakashan Chellattan Veettil ◽  
Stijn Speelman
Keyword(s):  
Social Networks ◽  
Technology Diffusion ◽  
Decisive Role ◽  
Marginal Groups ◽  
Informal Leaders ◽  
New Varieties ◽  
High Yielding Varieties ◽  
Caste Groups ◽  
Dissemination Of Technology ◽  
The Village

Social networks influence technology diffusion but targeting formal leaders (institutional central nodes) may lead to distributional consequences. This paper analyzes the role of informal social networks in technology diffusion in a socially hierarchical caste-based society. Often, information flow and technology diffusion are constrained by social and economic boundaries where informal nodes such as caste play a very decisive role in everyday life. Proper targeting and dissemination of technology to the marginalized sections of society are very important for their development. We observed that only one-fourth of farmers cultivate newer varieties which include hybrids and recently released high yielding varieties. The results showed that individuals belonging to marginal groups are influential and act as informal leaders when they are the dominant caste in the village. Progressive farmers are found to fail in disseminating new varieties, and targeting influential informal leaders who belong to the dominant caste of the village appears to be a better strategy. Among non-dominant caste members, influential leaders belonging to Other Backward Classes (OBCs) or Scheduled Tribes (STs) are more desirable targets than other caste groups. The more concentrated a network is in terms of its caste composition, the faster will be the spread of any technology.

Codiffusion of Technologies in Social Networks

2020 ◽  
Vol 12 (4) ◽  
pp. 193-228
Author(s):  
Natalia Lazzati
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Diffusion Process ◽  
Technology Diffusion ◽  
Consideration Sets ◽  
Network Structures ◽  
The Social ◽  
Over Time

This paper studies the diffusion process of two complementary technologies among people who are connected through a social network. It characterizes adoption rates over time for different initial allocations and network structures. In doing so, we provide some microfoundations for the stochastic formation of consideration sets. We are particularly interested in the following question: suppose we want to maximize technology diffusion and have a limited number of units of each of the two technologies to initially distribute—how should we allocate these units among people in the social network? (JEL D83, O33, Z13)

Multilayer Social Networks

2016 ◽  
Author(s):  
Mark E. Dickison ◽  
Matteo Magnani ◽  
Luca Rossi
Keyword(s):  
Social Networks ◽  
Multilayer Social Networks

Hostility and Perceptions of Support in Ambiguous Social Interactions

2006 ◽  
Vol 27 (2) ◽  
pp. 108-115 ◽  
Author(s):  
Ana-Maria Vranceanu ◽  
Linda C. Gallo ◽  
Laura M. Bogart
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Information Processing ◽  
Social Interactions ◽  
Social Information Processing ◽  
Perceived Social Support ◽  
Social Information ◽  
Inverse Association ◽  
Processing Bias ◽  
Information Processing Bias

The present study investigated whether a social information processing bias contributes to the inverse association between trait hostility and perceived social support. A sample of 104 undergraduates (50 men) completed a measure of hostility and rated videotaped interactions in which a speaker disclosed a problem while a listener reacted ambiguously. Results showed that hostile persons rated listeners as less friendly and socially supportive across six conversations, although the nature of the hostility effect varied by sex, target rated, and manner in which support was assessed. Hostility and target interactively impacted ratings of support and affiliation only for men. At least in part, a social information processing bias could contribute to hostile persons' perceptions of their social networks.

Sign in / Sign up

Export Citation Format

Share Document