WIREs Climate Policy and Governance: Who Cites Which Journals/Books?

Following up on yesterday's post on the WIRES Climate Change Policy and Governance topic, I'm taking a look at the same data (thirty eight articles) from a new angle: which journals, books, and other sources they cite in common.

The top ten sources cited (all of which are journals) are presented in the table below.

Top Ten Journals Cited in WIREs Climate Change Policy and Governance articles.

The significance of these journals is clear in the network visualization below, with the top journals clearly visible in the center.

WIREs Policy and Governance articles (red) and the journals, books, and other sources that they cite (blue).

One interesting point to note is that some journals get a large percentage of their citations from a few papers. For example, Friman and Standberg 2014, which focuses on historical responsibility for climate change, cites the journal Climatic Change nine times, almost a third of that journal's thirty two overall citations. This seems to be due to important articles on historical responsibility that have been published in Climatic Change.

The journal Climatic Change gets around 30% of its citations from one article (Friman and Sandberg 2014).

To illustrate the pattern of some journals being cited more times per article, the chart below shows the top ten cited journals by both the number of WIREs articles citing them (horizontal axis) and the number of times they are cited overall (vertical axis, includes multiple cites by a single paper).

Number of WIREs article citing a journal (horizontal axis) versus the number of times cited overall (vertical axis), with illustrative examples.

Finally, the data for all sources that were cited by at least two WIREs Policy and Governance articles:

Studying Climate Policy and Governance: Mapping Citations

I have recently been thinking about network analysis and visualization as a research analysis tool. One of the ideas I have been considering is mapping citations within individual journals when reviewing the academic literature.

To explore this possibility, I took a relatively small sample of thirty eight articles, which came from the Climate Change Policy and Governance topic in the journal Wiley Interdisciplinary Reviews: Climate Change (WIREs Climate Change). I limited the analysis to articles that a) are included in the Scopus database and b) have their references listed there. 

These articles had a total of 2,364 references. Of these, 106 were cited by at least two of the WIREs Climate Change articles. I used this data, Gephi, and the SciencesPo MediaLab's Table2Net tool to create a network visualization which connects two WiREs articles if they cite at least one source in common.

In the following network visualizations, article 1 and article 2 are connected if they share at least one reference in common.

The analysis results in the network below, which includes the thirty two articles that share a reference with at least one other article in the sample. The thickness of a connection shows the number of references in common (Branger et al. 2015 and Laing et al. 2014 at the bottom share nine references in common). The size of each circle shows the total number of shared references an article has (the two largest, Munck af Rosenschold et al. 2014 and Gupta 2010, share twenty one references each with other articles).  

Climate Policy and Governance Articles connected by shared references.

In the following two images, I show two ways of categorizing these articles. The first is based on WIREs Climate Change's own sub-topics, which divide the articles according to their focus (e.g., national policy or private governance). As the map shows, these sub-topics are relatively fragmented across the network.

Climate Policy and Governance Articles: Shared references, color coded according to WiRES Climate Change sub-topics.

The second image below organizes the articles into "communities" based on shared references. Most of these communities include articles from a number of WIREs sub-topics (for example, the yellow community includes articles from the multilevel/transnational, national, international, and cities sub-topics).

Climate Policy and Governance Articles: Shared references, color coded according to network "communities" identified by Gephi.

For now, I'm going to leave the analysis at the descriptive level, but I'm planning to come back to these articles in the near future.

Crossing the 1°C threshold: Science, symbolism, and climate politics

New Scientist magazine recently published an article showing that the world is on track to reach 1°C of global average warming above pre-industrial temperatures in 2015 (in this case, the average from 1850-1899). This is halfway to the 2°C warming limit which has been agreed to in international negotiations under the United Nations Framework Convention on Climate Change. It is also two thirds of the way to the stricter 1.5°C limit which some countries, notably small island nations, have argued is necessary. The 1°C 'milestone', if it is reached, will come in the same year as the crucial Paris climate negotiations, which aim to secure a global deal to reduce emissions and adapt to climate change.

Source: New Scientist

In many ways, there is not an important distinction between 1°C in 2015, 0.9°C in 2014, or 1.1°C in the future. However, as a researcher studying climate politics, I am very interested to see if and how crossing the 1°C threshold is understood in international negotiations, national policy debates, and the media.

In other words, how will 1°C of warming be framed? Will it be mentioned in media accounts alongside the 2°C limit and the rising concentrations of greenhouse gases in the atmosphere? Will national governments, NGOs, and other political actors such as the European Union refer to 1°C when pushing for more stringent emissions reductions?

And of course, if it is mentioned in policy debates, will this milestone have any effect? It is notoriously difficult to untangle the political effects of ideas and symbols. The most famous example of such an idea attracting a large amount of attention in environmental negotiations is the hole in the ozone layer which was detected during negotiations to limit emissions of ozone-depleting substances. Many participants in those negotiations mentioned the effect the ozone hole's discovery had on them. But even in this case, political scientist Edward Parson has raised doubts that the ozone hole had an important political effect. So studying the 1°C  and its political effects will be difficult.  

On a personal note, when we do 'officially' cross the 1°C threshold, I feel as if a door is symbolically closing on the world I grew up in. Again, I don't believe there is any significant scientific difference between 0.9°C and 1°C. Its importance is symbolic.

And hopefully that symbolism, of climate change being in 'the here and now', will provide a push, however minor, for ambitious climate change policy. 

A (Network) Map of the World

A quick post today...

About this time last year, I created a network map of Europe re-imagining the continent as a social network. Below is a network map for the entire world, showing all countries recognized by the United Nations who share at least one land border with another country. Country node sizes are based on the number of borders they have, and their colors are based on their continent (using the seven continent model common in the United States). The flipped orientation is due to the layout algorithm I used in Gephi.

Full size image available here

Who is Studying What? An Anatomy of Climate Change Think Tanks in Europe

Note: This post's underlying data and an acronym key are available here. Network data files (nodes, edges, GDF, Gephi) are available by request by sending an email to bpmoore@gmail.com. This is a work in progress, feedback is greatly appreciated.

The International Center for Climate Governance has built a fascinating database and map of climate change think tanks on every continent. Each think tank is classified according to nine research fields (e.g., adaptation, policy and institutions, forestry and land use, etc.).

I was curious to see which research fields were most popular among climate think tanks in Europe, and how the organizations themselves related to one another. There are 141 European think tanks listed on the website, and each organization is linked to between two and six research fields. The most common research field is Policy & Institutions (a focus of 85% of the think tanks), and the least common is the Carbon Finance field (27%):

Among the think tanks, which ones work on the same research issues? To explore this question, I first converted the ICCG data into an affinity network which contains two types of nodes: think tanks and research fields. In this type of network, a think tank can only be connected to one or more research fields, not to other think tanks. The result is shown below, illustrating the central position that research fields such as Policy and Institutions play in the climate think tank idea ecosystem, as well as the fields such as sustainable cities which attract less attention:

My one issue with this affiliation graph is that it does not directly show when two think tanks are working on similar issues. I therefore created a second, projected graph, which removes the research field nodes and connects two think tanks directly if they share at least one research field in common:

Using Gephi, I identified three highly-connected communities within the overall think tank network (color coded green, blue, and yellow). However, as should be obvious, there is not a clear-cut separation between these communities. This is because almost all of the think tanks are connected to each other. In fact, this network has a very high density, .975 out of 1, meaning that in this case almost all of the possible connections between think tanks actually exist. In addition, the network has a very high average clustering coefficient (.98), which measures how likely it is that any three nodes are connected to each other.

Finally, for those interested in the networks of specific European regions, the image below highlights think tanks from six regions (the British Isles, German-speaking Countries, Mediterranean Countries, Nordic Countries, the Low Countries, and Eastern European Countries):    

Below are each of the six regional networks, removed from the overall graph to highlight their unique structures and connections.

United Kingdom and Ireland

Germany, Switzerland, & Austria

Italy, Spain, Portugal, & Greece

Norway, Sweden, Denmark, & Finland

Holland and Belgium

Hungary, Lithuania, Poland, & the Czech Republic

The IPCC as a Social Network: The Working Group I Summary for Policymakers

Just a quick post to get this blog going again. Below is a network map of the authors of three chapters of the Intergovernmental Panel on Climate Change from the 3rd, 4th, and 5th Assessment Reports (released in 2001, 2007, and 2013, respectively).

The chapter in question is the Working Group I Summary for Policymakers, the working group dealing with the physical science of climate change. There are 151 authors pictured in the image, with 26 of those authors writing for more than one Assessment Report. Four authors (in the center) were involved in all three years. A red connection means that that author was a Lead Author in that year, a blue connection denotes Contributing Authors.

By my count, 24 of the 26 (92%) "multi-report" authors are from Annex I (industrialized) countries. This includes all four authors in the center of the image.

Visualizing the UK National Ecosystem Assessment

For my recent master's dissertation, I studied the UK National Ecosystem Assessment (UK NEA), a government-initiated scientific assessment of the UK's ecosystems, their value to society, and policy options for their protection. One of the biggest challenges when researching an assessment of this type is keeping track of the large number of contributors involved. In the case of the UK NEA, the contributors numbered upwards of 500 people. In a process where some authors contributed to multiple chapters, keeping track of everyone and their relationships to each other is difficult.

To handle this complex situation, I used Gephi to create a network map which presents the UK NEA's authors as a social network held together by co-authorship. Using author data from the Assessment itself, I was able to create a map which included all 403 people who were listed as authors for at least one of the UK NEA's chapters.

UK NEA Authorship Network Map

The image above is based on a very simple foundation. Each circle represents one of the UK NEA's authors. A connection between two authors means that they co-authored at least one chapter together. In the center of the network, purple connections identify authors who co-authored the high-level Synthesis for Policy Makers. Magenta connections represent co-authorship of the Assessment's introductory chapters, while green connections represent habitat-based chapters that focused on specific types of ecosystems such as woodlands or freshwaters. Light green connections (found at the bottom of the image) are related to ecosystem services chapters, and gold connections signify country-focused chapters (in this case the four constituent countries of the United Kingdom: England, Scotland, Wales, and Northern Ireland). Finally, blue connections are related to ecosystem service valuation and scenario building (the valuation aspect of the UK NEA was the main focus of my dissertation research).

So what insights, if any, does this network map provide? First, the map confirms - and visualizes - a number of features of the UK NEA authorship network that I noticed during my research. For example, many of the authors were involved in only one chapter of the assessment, and these groups form dense, easy-to-distinguish clusters within the network. Connecting these clusters are a relatively small number of multi-chapter authors, as can be seen here in this close-up:

Author Clusters with Two "Connector" Authors (Center)

Second, the map helps illustrate the relationship between chapters written mainly by ecologists (green connections) and other chapters largely written by economists and social scientists (blue connections). Some ecology-focused chapters were relatively closely connected to the valuation chapters because they included ecologists or economists who also worked on ecosystem service valuation (Clusters A and B below). Other ecology chapters were not connected directly to the valuation chapters (Cluster C). Why the difference? This topic was not my focus, but it could be an interesting one to explore.

Ecology Chapters and Their Connection to Valuation Chapters

However, I believe that these network maps may be most useful for identifying effective research strategies. For example, if a researcher was studying interdisciplinarity in scientific assessments, they could use the network map above to identify the UK NEA authors who connected different chapters. They could then request an interview with these "connector" authors in order to learn more about the process of exchange both between chapters and between academic disciplines.

So, is creating a network map worth the time investment? (around 10-15 hours for the UK NEA map above) The answer depends on the research questions being pursued. But given the (relatively) easy learning curve for network software like Gephi, network visualization could be a valuable addition to researchers' intellectual toolkit.