Exploring Social Media Knowledge as a Means for Fighting Corruption in CEE Countries
Keywords:social media, Corruption, CEE, Knowledge, Regression Analysis
It is evidently seen that social networks are assessed widely in recent times as a means of sharing knowledge, and more importantly, resist control from influential entities compared to the regular media. Social media fight corruption by making information readily available in the form of analysis, endorsements, and through campaigns and collaboration. For this reason, some researchers are increasingly interested in how knowledge of social networks impacts our society leading to corruption reduction. In this paper, we explore the contribution of the knowledge of social media networks in reducing corruption within CEE countries. Regression analysis is employed to analyze an eighteen-year panel data (from 2002 to 2020), using secondary data from the World Bank, the World Press Freedom Index, and Transparency International of the selected CEE countries. We analyze social media variables such as social media usage, cultural tightness looseness (CTL) as independent variables and used press freedom, political stability index, and GDP per capita as control variables. Also, with corruption as a dependent variable, we used control of corruption index (CCI) and corruption perception index (CPI) to ascertain the social media network effect on corruption reduction. This article contributes to the existing knowledge by discovering the unique role that social media knowledge plays in reducing corruption in CEE countries. The result has shown that both social media usage and CTL significantly affect corruption and its reduction. In addition, it allows us to propose some practical implications for policymakers.
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