Government Engagement with the Civic Tech Community on Twitter: The Case of the New York City School of Data

Crystal R. Charles, J. Ramon Gil-Garcia
Sept. 13, 2018

Abstract

Social media in government has been “defined as a group of technologies that allow public agencies to foster engagement with citizens and other organizations” (Criado et al., 2013, p. 320).

It has been researched as a way for public organizations to innovate, share information, and build relationships (Criado et al., 2013, p. 319).

In the Information Age, it is important for government to keep moving forward in its information policies and technologies. Part of the salience of studying government use of social media is that it is increasingly a place where political and social activism occurs or begins (Sandoval-Almazan & Ramon Gil-Garcia, 2014; Sørensen, 2016).

One final aspect of social media use by government and the public is trust; civic engagement through social media may build trust in insitutions (Warren et al., 2014). This current context provides us with the impetus for the study discussed in this paper.

This study aims to answer the question: What role does government play in public deliberation about civic tech on Twitter?

This question is grounded in developments in the field of deliberative democracy. This is also a timely question, since the internet and social media are ubiquitous. While there are studies on social media (Ediger et al., 2010; Huberman et al., 2008; Marinelli & Gregori, 2015) as well as studies that apply deliberative democracy to the case of social media (Heatherly et al., 2016; Sørensen, 2016; Wiklund, 2005), there is more work to be done in unpacking the nuances of the theory and of using social media applications in government.

So far studies and theoretical debates have stayed at the macro level, trying to test the public discourse argument as a whole.

This means that it is necessary to apply deliberative democracy to the micro level of how government agencies can adapt their social media to facilitate deliberative democracy and unpack the nuances of the language used in social media posts according to the normative deliberative standard of public communication.

This study uses the case of a Twitter network of actors who used a specific hashtag, #NYCSoData, while attending and discussing a conference on topics in civic tech. The data collected includes retweets, mentions, profile information, as well as the texts of the tweets, which is what allows for a content analysis.

The focus of this paper is on the preliminary results of the social network analysis.

The operationalizations of the social network analysis measures used to answer the research question are informed by the dialogic perspective, integrated as a complementary framework from the field of Communication, as well as a previous similar study done by Rethemeyer & Hatmaker (2008) on emails between actors in multiple sectors.

Preliminary results indicate that local government plays a relatively prominent role in the network, interacting with actors from multiple sectors.

These results lead to questions about how government participation in the online sphere might impact the traditional public sphere.

This five-part paper continues in the second section with an overview of the recent theoretical developments in deliberative democracy, focusing on the application of the dialogic perspective.

The dialogic perspective distinguishes between one-way and two-way types of online communication, and the implications those differences may have in practice and online discussion.

 The third section explains the social network analysis methods, content analysis methods, and case.

The mixed-method research design will allow us to gain a more comprehensive understanding of the structure of the network and the relative position of government, and to understand some of the nuances of the interactions and how different actors used the content of the Twitter posts to engage with each other.

The fourth section discusses the preliminary results of the social network analysis.

 

The fifth section concludes with next steps.