Citizens’ Use of Social Media in Government, Perceived Transparency, and Trust in Government

ABSTRACT:

Governments are adopting social media to provide complementary information dissemination, communication, and participation channels whereby citizens can access government and government officials and make informed decisions. Using 2009 national e-government survey data from the Pew Research Center, this study finds (1) that use of government social media is significantly and positively associated with perceptions of government transparency, (2) that perceptions of government transparency are positively and significantly related to trust in government, and (3) that perceptions of government transparency mediate the relationship between use of government social media and trust in government. These findings demonstrate that social media is an effective means for government to improve citizens’ trust in government by enhancing their perceptions of government transparency. The study contributes to the literature by providing empirical evidence of the mediating role of perceived government transparency in linking the use of e-government to trust in government.

KEYWORDS::

• perceived transparency
• social media in government
• trust in government

Notes

The estimation methods in CB SEM (generalized least squares and maximum likelihood) require normally distributed data. An alternative method—asymptotically distribution free—can be used to estimate parameters using non-normally distributed data in CB SEM, but a very large sample size (e.g., over 2,500) is needed and its ability to handle missing data is limited. Furthermore, CB SEM has limited ability to identify a model that includes formative latent variables; even programs like AMOS do not accept a model specification for a latent variable with multiple formative indicators (Blunch, 2008). While some scholars point out that CB SEM (e.g., LISREL, EQS, AMOS) was created only to handle reflective indicators (Chin, 1998), it is not impossible for CB SEM to include formative indicators (Jöreskog & Goldberger, 1975). However, identifying a model with formative constructs is not easy due to restrictive identification conditions (Bollen & Davis, 1994; Diamantopoulos, Riefler, & Roth, 2008; Jöreskog & Goldberger, 1975; MacCallum & Browne, 1993). For example, the MIMIC models suggested by Jöreskog and Goldberger (1975) require a specification of at least two additional reflective indicators; similarly, the so-called “2 + emitted paths rule” applies to modeling formative constructs (Diamantopulos et al., 2008). The research model in this study does not satisfy these conditions or rules, thus making it impossible to use CB SEM.

Additional information

Notes on contributors

Changsoo Song

Changsoo Song is an evaluation specialist at the Social and Behavioral Sciences Research Consortium at the University of Nebraska–Lincoln. He received his Ph.D. in Public Administration from the University of Nebraska at Omaha. His research/professional interests include information management and policy/program evaluations in the public sector. His current evaluation research projects include government and non-profit programs to reduce minority health disparities and to prevent substance abuse among youth. He has presented papers at domestic and international conferences, including Public Management Research Conference, Annual Conference of the Association of Public Policy Analysis and Management, and International Conference of the Korean Association of Policy Analysis.

Jooho Lee

Jooho Lee is an Associate Professor at the School of Public Administration at the University of Nebraska, Omaha. Areas of his research interest include public management, with emphasis on information and communication technologies (ICT) use in public organizations and application of social network theories in public management issues such as interagency and interorganizational collaboration. He has been doing research on the antecedents and consequences of ICT adoption by government and the public. His research has appeared in public administration and electronic government journals such as Public Administration Review, American Review of Public Administration, Administration and Society, and Government Information Quarterly. His current research projects include the antecedents and consequences of interagency networks, citizen participation programs, and social media adoption by citizens. He earned his Ph.D. in Public Administration from the Maxwell School of Citizenship and Public Affairs at Syracuse University.