Corruption is in the fabric of societies

Many think that corruption is a result of wealth or the lack of it. Some assume that tighter regulations might stop corruption. Hence, socio-economic metrics have been used to explain the level of corruption in different places with different regulatory regimes.

In our recent work, we show that corruption is in the fabric of the societies and the structure of the social networks in cities are highly related with the chance of corruption. Certain characteristics of a towns’ social ties, such as fragmentation or diversity of residents’ connections, measured via an online social network, predict corruption in local government contracting above and beyond socio-economic variables.

Here is the abstract of the article:

Corruption is a social plague: gains accrue to small groups, while its costs are borne by everyone. Significant variation in its level between and within countries suggests a relationship between social structure and the prevalence of corruption, yet, large-scale empirical studies thereof have been missing due to lack of data. In this paper, we relate the structural characteristics of social capital of settlements with corruption in their local governments. Using datasets from Hungary, we quantify corruption risk by suppressed competition and lack of transparency in the settlement’s awarded public contracts. We characterize social capital using social network data from a popular online platform. Controlling for social, economic and political factors, we find that settlements with fragmented social networks, indicating an excess of bonding social capital has higher corruption risk, and settlements with more diverse external connectivity, suggesting a surplus of bridging social capital is less exposed to corruption. We interpret fragmentation as fostering in-group favouritism and conformity, which increase corruption, while diversity facilitates impartiality in public life and stifles corruption.

rsos182103f04
Ego networks with low (a) and high (b) diversity. Colours indicate membership in detected communities in the ego network. Circles denote users from the same settlement as the ego, while triangles mark users from elsewhere. The high diversity user’s network has clusters of alters mostly from different settlements.

Published by Taha Yasseri

Associate Professor, School of Sociology, University College Dublin

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