Visualising Cyber Diplomacy Voting

TL/DR: This page contains vote tables, world maps and network diagrams that accompany the article Cyber Diplomacy: A New Way Visualise UN Voting Records. At the end is a Q&A section with more detailed information for those planning to use the resources to do their own mapping or analysis.

Voting record data

Excel file with voting records from the six votes that are included in the visualisation article and this resource page.

Maps of votes

Map of 2012 World Conference on International Telecommunications(WCIT) vote on a revised International Telecommunication Regulation (ITR)
Map of 2018 UN vote on a cybercrime resolution proposed by Russia
Map of 2018 UN vote on an Open Ended Working Group resolution proposed by Russia
Map of 2018 UN vote on a UN Group of Governmental Experts resolution proposed by United States
Map of 2019 UN vote on an open-ended Cybercrime Ad Hoc Committee resolution proposed by Russia
Map of 2020 UN vote on an Open Ended Working Group (2021-25) resolution proposed by Russia

Network diagrams of votes

The following pair of charts illustrates how I converted a network generated in Gephi to the nodes in Flourish. In the Gephi diagram, each UN member is represented by a node and the lines between them represent occasions when two countries voted the same way. Although hard to tell at this scale, the more times two countries voted the same way the thicker the line between them is. Having generated the node positions in Gephi I moved them across to Flourish and applied labels and colours depending upon the information within the network I wanted to illustrate.

Gephi version of the UN 2018-2020 vote network visualisation
Network diagram of UN cyber diplomacy votes 2018-2020 generated by Gephi
Flourish version of the UN 2018-2020 vote network visualisation


Q. How does the Gephi algorithm position nodes in these charts?

A. The network diagram software Gephi uses algorithms to position the nodes using a combination of attracting and repelling forces, the strength of which can be set by the user.  I applied the Force Atlas algorithm with a repulsion of X and attraction of Y. With this algorithm, unconnected nodes repel each other like particles, while nodes that are connected (by edges) attract each other as if joined by a spring. The algorithm’s authors provide an explanation of its working in the journal PLOS ONE.

Q. Why do you include and exclude the votes you do in your visualisations?

A. The votes I chose to include are those where the UN member states were divided in their opinions on the resolution. This was in line with wanting to visualise national positions on the issues in cyber diplomacy that are most hotly contested. Such an approach highlights the differences between national positions in any visualisation and underplays the reality that consensus that has been reached on many issues.

Q. Why do you group the rounds of votes as you do into WCIT, UN(18) and UN(20)?

A. As I explain in the article voting behaviour in WCIT is not closely correlated with voting in the 2018-2020 resolutions, except for countries that deliberately chose not to sign up to the new regulations. I therefore treat the WCIT vote as distinct from the UN votes. Within the five UN votes I think it can be helpful to look at the three in UN 2018 as a specific sub-set because most countries were considering these three together as they decided how to vote in a key year. I therefore produce visualisations that look at just 2018 and then look at all the votes from 2018 to 2020.

Q. Why do you group First Committee (cyber security) and Third Committee (cybercrime) votes together?

A. Useful analysis can be conducted by looking at these votes separately. However, in my article I wanted to demonstrate how larger voting records could be visualised and for that it made sense to group the two sets of votes under the umbrella of ‘cyber diplomacy’. I think this is legitimate because the two tracks of cyber diplomacy cross reference each other and are other dealt with by experts who are working on both and consider their national positions holistically across the two. Whether you think it is useful to combine the two may depend upon the extent to which you believe countries are voting for or against alternative visions for the Internet(s) and government influence in it, as opposed to the specifics of the specific resolution before them.

Q. What does it mean to say that a country voted “with Russia” or “with the United States” on a resolution?

I use this phrasing only to mean that a country voted the same way on a resolution as one of these countries. I refer to these two countries because they are the two that have proposed the resolutions being voted upon in the 2018 to 2020 window. Obviously Russia and the United States are also important influencers of cyber diplomacy with competing visions for government involvement in the Internet(s), but in my article I have tried to confine my discussion to methodologies for visualising voting records and not questions of influence and why countries voted as they did. Importantly, just because two countries vote the same way on a resolution it does not necessarily follow that they share a policy position and are like-minded. There can be many reasons why a country voted as they did or were absent for a vote.