INTERVENTIONS IN SOCIAL NETWORKS: IMPACT ON MOOD AND NETWORK DYNAMICS

Danica Vukadinović Greetham (), Abhijit Sengupta, Robert Hurling () and Joy Wilkinson ()
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Danica Vukadinović Greetham: Centre for the Mathematics of Human Behavior, University of Reading, RG6 6OW, UK
Robert Hurling: Unilever R&D Colworth, UK
Joy Wilkinson: Unilever R&D Colworth, UK

Advances in Complex Systems (ACS), 2015, vol. 18, issue 03n04, 1-32

Abstract: Results from two studies on longitudinal friendship networks are presented, exploring the impact of a gratitude intervention on positive and negative affect dynamics in a social network. The gratitude intervention had been previously shown to increase positive affect and decrease negative affect in an individual but dynamic group effects have not been considered. In the first study, the intervention was administered to the whole network. In the second study, two social networks are considered and in each only a subset of individuals, initially low/high in negative affect respectively received the intervention as "agents of change". Data was analyzed using stochastic actor-based modeling techniques to identify resulting network changes, impact on positive and negative affect and potential contagion of mood within the group. The first study found a group level increase in positive and a decrease in negative affect. Homophily was detected with regard to positive and negative affect but no evidence of contagion was found. The network itself became more volatile along with a fall in rate of change of negative affect. Centrality measures indicated that the best broadcasters were the individuals with the least negative affect levels at the beginning of the study. In the second study, the positive and negative affect levels for the whole group depended on the initial levels of negative affect of the intervention recipients. There was evidence of positive affect contagion in the group where intervention recipients had low initial level of negative affect and contagion in negative affect for the group where recipients had initially high level of negative affect.

Keywords: Longitudinal networks; stochastic actor modeling; Katz centrality; positive and negative affect; network interventions (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S0219525915500162

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