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37. Negative ties in social networks


shutterstock_101202193tree-shadowsWe are all immersed in networks. We have networks of friends, family, and work associates plus many other types of social connection. A social network is a collection of individuals together with a social relationship which connects pairs of people together. Social networking sites such as facebook and LinkedIn are now familiar tools we use in everyday life as one way of maintaining and exploiting the networks we are in. Social network analysis takes these networks and looks for structural properties which help explain social phenomena. For example, are people who are more central in a friendship network in a company more likely to stay with the company long term? Or is it the case that people with more friends are happier than those with few friends? We are also interested in how networks form and how things move through the network. For example, the spread of rumours or sexually transmitted diseases. Do different network structures facilitate or prevent either of these from spreading?

Social network analysis has developed a set of tools to visualise and analyse data that can be expressed in network form. These tools have nearly always assumed that the connections between the individuals are positive in nature. Negative ties refer to relations that represent negative sentiments or behaviours towards other people in the network.  We note that our interest is specifically in relations that are in themselves negative, rather than positive relations that may have negative consequences. For example, positive relations may enable the flow of useful ideas and emotional support, but may also transmit disease and misinformation. Negative relations are things like dislikes, fights with other or disrespectful behaviour.

Martin Everett in Manchester’s Mitchell Centre working with Steve Borgatti at the University of Kentucky has developed a collection of techniques specifically designed to help us analyse networks that contain negative ties. This continues Manchester’s strong association with networks and innovative methods.


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