Protest engagement: weak vs strong social ties


This article dwells upon the importance of finding methods and ways of studying protest behaviour that can explain its emergence. Protest behaviour is considered as the result of protest engagement. It is assumed that there are social ties between individuals, potential protesters. M. Granovetter proposes to distinguish strong ties and weak ties. Strong ties tend to form closed and cohesive groups but weak ties can be the bridges that match groups and/or individuals. The author of this article conducts a research with applying a method of agent-based modelling. Its aim is to test the Granovetter’s thesis about the strength of weak ties towards protest behaviour. In this research the linear threshold model is used. Our research with applying method of the agent-based modelling includes the computer experiments (simulations) with the social networks. There are generated five networks, three of which contain only strong ties and the rest of the networks contain only weak ties. Simulations with the networks allow us to determine the number of inactive agents that are involved in the protest, the speed of the protest engagement and the effectiveness of overcoming the resistance of inactive agents. It is found that both weak ties and strong ties can determine protest behaviour. Strong ties contribute to a quicker protest engagement. Weak ties can better overcome the resistance of inactive agents. At the same time weak ties slow down the process of the protest engagement and strong ties are generally less effective in overcoming the resistance of inactive agents. Agent-based modelling helps us to conduct the fundamental research. On the one hand we test Granovetter’s thesis about the strength of weak ties towards protest behaviour. On the other hand we cannot draw conclusions about protest behaviour in Ukraine. But we can conduct an empirical sociological study in order to test the results of our research and understand its relevance towards protest behaviour in Ukraine.

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