I am an Associate Professor of Public Administration at the Maxwell School of Citizenship and Public Affairs, Syracuse University, NY. In my research projects I am focusing on informal social networks in the public sector and the use of social media applications by government organizations. I teach classes on social media management, digital government, public management, and social network analysis.
Open collaboration has evolved as a new venue for innovation creation in the public sector. Government organizations are using online platforms to crowdsource and co-produce public sector innovations with the help of external and internal problem solvers. Most recently the U.S. federal government has allowed agencies to collaboratively create and share open source code on the social coding platform Github. A community of government employees is sharing open source code for website development, data sources, but also draft policy documents on Github. Quantitative data extracted from Github’s application programming interface is used to analyze the social network relationships between contributors to government code and the reuse of open government tools developed on Github. In addition, qualitative interviews with government contributors in this social coding environment provide practical insights into new forms of co-development of open source code and policy drafting in the public sector.
I also posted the full paper to SSRN. I’m still adding more interview data and need to do a more sophisticated network analysis before I can send this paper out for review. I would appreciate any feedback people might have to improve the paper.
Elsevier just provided a new service to authors: A dashboard showing how often your article was viewed during the first year. I was pleased to see that over 1,400 people at least clicked on the article. It’s a bit of a vanity thing seeing that there is some interest in your work. Interestingly enough it doesn’t reflect how often the article was then also cited in those authors’ work. This certainly has to do with the time lag in the publication process – I expect citations with a lag of 2-3 years, but I wonder if this might also reflect the learning process of other authors and has little to do with the actual decision to cite:
Clayton Wukich and I presented a paper at the annual American Political Science Conference (APSA) in DC last week. We analyzed three communication modes state emergency managers use in all phases of emergency management. The working paper is available on SSRN:
Wukich, Clayton and Mergel, Ines A., Closing the Citizen-Government Communication Gap: Content, Audience, and Network Analysis of Government Tweets (August 28, 2014). Available at SSRN: http://ssrn.com/abstract=2488681
I wrote a paper providing empirical evidence for a phased adoption framework of social media adoption in government that we published in 2013 in PAR. This new paper shows how government agencies move through stages of institutionalizing new technologies and how they adapt their internal standard operating procedures to reflect the changes in the way citizens interact with government.
Social media adoption is oftentimes seen as technologically determined by third parties outside of government, with government’s role limited to reactively jump on the bandwagon and respond to citizen preferences. However, social media interactions are emergent and challenging existing bureaucratic norms and regulations. This paper provides empirical evidence for the institutionalization stages government agencies’ move through when they are adopting new technologies. Adoption occurs at varying degrees of formalization and not all departments in the U.S. executive branch regulate and restrict the use of new technologies in the same way. The internal procedural and organizational changes that occur during the adoption process are extracted using qualitative interviews with social media directors in the 15 departments which received the executive order to “harness new technologies” in order to make the U.S. government more transparent, participatory and collaborative. In addition to the perceptions of federal social media directors, a process tracing approach was used to map the accompanying governance and institutional changes and follow-up orders to direct the adoption of social media. Tracing both the behavior of individual organizations as well as the institutional top-down responses, this paper is both relevant for academics as well as practitioners. It provides the basis for future large-scale research studies across all levels of government, as well as insights into the black box of organizational responses to a top-down political mandate.
This new report addresses the key question of how government should measure the impact of its social media use.
Social media data – as part of the big data landscape – has important signaling function for government organizations. Public managers can quickly assess what citizens think about draft policies, understand the impact they will have on citizens or actively pull citizens ideas into the government innovation process. However, big data collection and analysis are for many government organizations still a barrier and it is important to understand how to make sense of the massive amount of data that is produced on social media every day.
This report guides public managers step-by-step through the process of slicing and dicing big data into small data sets that provide important mission-relevant insights to public managers.
First, I offer a survey of the social media measurement landscape showing what free tools are used and the type of insights they can quickly provide through constant monitoring and for reporting purposes. Then I review the White House’s digital services measurement framework which is part of the overall Digital Government Strategy. Next, I discuss the design steps for a social media strategy which will be basis for all social media efforts and should include the mission and goals which can then be operationalized and measured. Finally, I provide insights how the social media metrics can be aligned with the social media strategic goals and how these numbers and other qualitative insights can be reported to make a business case for the impact of social media interactions in government.
I interviewed social media managers in the federal government, observed their online discussions about social media metrics, and reviewed GSA’s best practices recommendations and practitioner videos to understand what the current measurement practices are. Based on these insights, I put together a comprehensive report that guides managers through the process of setting up a mission-driven social media strategy and policy as the basis for all future measurement activities, and provided insights on how they can build a business with insights derived from both quantitative and qualitative social media data.
By now the major social media failure of New York Police’s social media department has made it around the world. The well-intended pull tactic to ask citizens to tweet their best memories and share pictures with NYPD using the hashtag #MyNYPD was by an overwhelming majority of Twitter users used to send in pictures of their worst memories:
I believe it was an honest attempt to use a tactic to actively engage citizens. Other government departments are extremely successful in asking citizens for their input or for sending in pictures, like the Department of Interior for example. There is research out there that shows that citizens feel more engaged and ‘heard’ when have options to directly get in touch with government officials through unofficial channels, such as social media.
However, what is interesting about this story is not so much that NYPD was surprised by the flood of negative images or might have misjudged the open culture of the Web. Instead, I find it much more interesting that NYPD won’t be able to rely on Twitter as a resilient infrastructure during emergency situations. Clearly, thousands of people in NY don’t trust the police in the first place and that has significant implications for outreach and preparedness messaging. If no one listens to you or even makes fun of you, how will you be able to create a trusted voice online? Who will listen in case of another hurricane that shuts down power lines? A recent Congressional hearing has shown that citizens’s cellphones were still connected to the Web and served as a lifeline during the power outage.
I believe this is an important lesson for NYPD to build a trustworthy online presence – in combination with the same offline trust of course – so that they can rely on social media during emergency situations. This has to be done between major events and not at times when citizens actually have be reached in an emergency. A tough road ahead for NYPD.
I put together a list of open government platforms that I used in my Digital Government class this semester at the Maxwell School of Citizenship and Public Affairs. The list is sorted by their contributions to the three dimensions of the 2009 Open Government and Transparency memo (transparency, participation, and collaboration). In addition, for each platform I thought about the main goals, the target audience (or engaged crowd), the process(es), and the potential outcomes.
I included HealthCare.gov even though it is an online marketplace and might not be considered as an Open Government initiative. However, I believe it increased transparency for both the (uninsured) public and journalists, as well as the providers in each state.
Addition: Alex Howard prompted me on Twitter to think about what kind of transparency the platform might provide. I include it in the class, because the platform served as a broker to help citizens understand their local marketplace and provide information about plans as well as providers. I believe it is a valuable and trusted government service and private marketplaces might not have the same level of trust. Take a look at Alex’s article on TechPresident where he discusses private healthcare markets.
I am posting it here as a summary for my class, but also to ask for feedback from anyone interested in this topic. Did I forget an important platform? Is the classification and my analysis of the dimensions reasonable? Should I add more dimensions to describe the platforms? Curious what you think, Internet!