Essays on Transparency and Trust in Government

In democratic societies, trust in government emerges as a fundamental pillar for ensuring effective governance. It not only fuels policy adherence and economic well-being but also serves as an indicator for the health of the democratic fabric of a nation. Recognizing its centrality, scholars and practitioners alike have been engaged in understanding the intricate dynamics between government transparency and citizen trust. Yet, as we delve into the vast body of literature, many gaps and inconsistencies emerge. The foundational paper in this dissertation conducts a comprehensive examination of the literature to explore the complex relationship between government transparency and citizen trust. Contrary to preconceived perceptions, transparency's impact on trust isn't a straightforward, universally accepted dynamic. While some assert that increased transparency can foster trust, others warn of the opposite effect. This theoretical divergence demands a nuanced understanding, one that is grounded in empirical investigation. The literature review not only shows some of the pathways through which transparency potentially impacts trust but also underscores the empirical gaps. Notably, many studies within this literature employ the same sources for gauging trust and transparency, inadvertently introducing the risk of common source bias. Addressing the identified gap, the second paper in this series offers a new perspective, taking the perspective beyond the mere content of disclosed government information. It explores the understudied process of citizens' responses to the act of disclosure itself. The paper's approach, rooted in a conjoint survey experiment, seeks to understand the nuances of public trust responses, emphasizing the type and motivation behind governmental information disclosure. However, as we explore the multifaceted relationship of trust and trust, it becomes relevant to question the metrics that inform our understanding. The reliance on same sources for measuring transparency and trust, as identified in the first paper, not only risks bias but also potentially misses the evolving patterns of public sentiment. This brings us to the third and final paper, which conducts an attempt to gauge public trust through social media data. By applying machine learning techniques and focusing on Twitter behavior, the study provides an alternative avenue to measure trust, capturing real-time, spontaneous public sentiments, although with several limitations. In essence, this dissertation, while acknowledging the inherent limitations of each method, attempts to push the boundaries of the understanding of trust in government and its relationship with government information disclosure.