Mapping the Publics of Public Finance

Team Members: Jonathan Gray, Anna Alberts, Cecile Le Guen, Eileen Wagner, Danny Lämmerhirt, Lucie Sedmihradská, Sergej Lugovic,

Introduction

While the topic of EU budget and spending affects citizens and policies across many areas, it is rarely broached in the media or in advocacy. Thus we have on the one hand stakeholders that could encompass an entire political spectrum, and on the other very few existing channels and platforms that would make traditional outreach meaningful. The publics that gather and disperse around particular issues in time would not be captured by the traditional methods. This report aims to provide guidelines and methods to map and engage with fluid stakeholders as well as publics around the issue of public budget taking test-cases of the EU-budget, the UK spending review, and the network of transparency organisations in the Czech Republic. The results of this report inform the development of Openbudgets.eu, an open data portal rendering the budget of the European Union more transparent, useable and understandable.

Aligned with the objectives of the Open Budgets’ project, this research employs digital methods of the DMI Winterschool in order to discover latent audiences and publics for the project OpenBudgets.eu and extend the current networks, and second, to concentrate on the known actors and target audiences of OpenBudgets.eu. The discovery of these audiences and publics requires a combination of conventional participatory stakeholder methods and new digital stakeholder mapping tools, that is digital methods. For this project a team of 9 students plus representatives from Open Knowledge Germany, Open Knowledge International, and the University of Economics in Prague worked together.

Initial Data Sets

We focused on two specific aspects of European budget: the overall European budget, that is the EU Budget and a specific part of this budget that amounts to about one third of the European budget: the European Structural and Investment Funds. For these two terms, correllating search queries in French, German, Czech, Dutch, and Italian have been identified to explore differences across Google's domains. Additionally we used a selection of Dutch, German and French media outlets in Lexis Nexis to identify media reporting. In order to identify actor alignments with the issue crawler, a URL list of lobby groups lobbying within the European Union's institutions on budget-related topics has been retrieved using the European Transparency Register. This list was complemented by an expert list of Czech advocacy organisations working on public spending. In order to analyse Twitter, a collection of 300,000 tweets has been gathered during the UK spending review in November 2015, allowing for a precise analysis of a national debate around budgets. This review was established in the late 1990s by then Chancellor of the Exchequer Gordon Brown in order to establish spending priorities and limits. The 2015 Spending Review was the first of its kind since the Conservative Party won the elections in May 2015, outlining “how £4 trillion of government money will be allocated over the next five years”.

The data set about the UK’s 2015 Spending Review had been collected in advance from 2015-11-25 11:00:00 to 2016-01-07 00:00:00. The hashtags “#AutumnStatement2015”, “#spendingreview”, “#SR15” were used to configure the capture on TCAT. This gave a total of 306,311 tweets from 118,714 distinct users.

Research Questions

The objective of this research is to study democratic engagement around public finances through the analysis of a variety of different digital platforms - including social media, news media and the web. We aimed at extracting and analysing data from different online spaces in order to get a richer empirical picture of who cares about public finances and what their interests are. Following this objective the research aims to answer following questions:

1) Who is engaged around fiscal policy on national or EU level on digital media? Which publics of fiscal policy are most prominent, and which are more marginal?

2) How are they engaged? And how might this engagement be studied?

Ultimately, we’d like to understand which kinds of topics are associated with fiscal policy in different online spaces - from climate change to migration to international development.

Methodology and Findings

Search engine results

Our search engine study was done on the following query terms related to the EU’s budget: The first step was to identify the official translation of these terms into the five languages that were examined: French, German, Czech, Dutch, and Italian. Next, research browsers in the respective languages were set up, and query results were documented in a spreadsheet. Two sets of data (["European Structural and Investment Fonds"] (short: ESIF) and ["EU budget"]) were then categorised according to the type of sectors the actors belonged to (public, private, CSO, media, research) and the level on which they operated (regional, national, EU). For the term “EU budget”, the additional category of issue/topic was used to specify the overall content of the site. This process is called “coding”. Results were visualised using color-coded lists (see figures 1a and 1b).

Figure 1a: Tracing “budget speak” in search engine results – top 30

Figure 1b: Tracing “budget speak” in search engine results – top 100

Lexis Nexis media mapping

For the media mapping with Lexis Nexis, we extracted and investigated news articles on the EU budget. We limited the results from the database to British and Dutch press in print, which means we downloaded all articles from Dutch, German, and UK newspapers between 2012 and 2015 that include the term ‘EU budget’ or, for the German and Dutch papers, ‘EU-Haushalt’ and ‘EU-begroting’ respectively. 1 The frequency of mentions can be seen in the following graph.

1https://newstories.atavist.com/why-brits-know-their-eu-budget-better-than-the-dutch

Figure 2: News coverage of the EU budget in the United Kingdom and in the Netherlands 2012-2015

There are only few articles about the EU budget in Dutch and English papers. However, as evidenced by the chart, there are some spikes in the number of articles written about the EU budget. This suggests that reporting on issues related to the EU budget are driven by larger events. When looking at the use of the terms in the United Kingdom and in the Netherlands, October and November 2012 stand out the most. There is a peak in early October when the British prime minister David Cameron made clear that he was not afraid to veto the proposal for the budget of the EU for the years 2014 to 2020, if the budget would increase above inflation. To a lesser extent this also caused a peak in the Dutch media, since a veto would have consequences for the entire EU.

As the EU summit of 22.-23.11 in 2012 came closer, the media kept reporting about the EU budget. Cameron stood by his position on the EU budget, and German chancellor Angela Merkel visited him on the 7th of November. In the build-up to the actual summit, Cameron was under political pressure in his own country. There is also more reporting in the Netherlands, as Dutch prime minister Mark Rutte backs Cameron in his stance on the budget. This would explain the peak on 22 and 23 November when the summit takes place. The negotiations failed, leading to extensive writing about what would happen next.

At the end of October 2014, there is a major peak in the United Kingdom, but not in the Netherlands. The reason: the United Kingdom had to pay an after-tax to Brussels, and Cameron refused. The Netherlands also had to pay, and they did, which means there was no commotion to report on.

A closer look at the kind of publishers reveals a difference in the quality of the articles. Whereas Dutch media offers fewer articles, they mostly come from specialist papers (AD, De Telegraaf, NRC Handelsblad, Trouw and de Volkskrant), while the British papers are often tabloids (e.g. The Sun, Daily Express, and Daily Mail). The dataset on LexisNexis also allows a detailed analysis of the authors of articles related to the EU budget. For example, Marc Peeperkorn and Stéphane Alonso are by far the more prolific Dutch reporters on the issue.

For the hyperlink analysis, we compared issue networks around Czech CSOs by top Google results and expert lists. We performed a simple co-link analysis and visualised the result in Gephy (see figures 3 and 4). It is evident that the relationship between CSOs in the expert list were much stronger than the one from the Google search results.

Figure 3: List of actors associated with “EU budget” in Google.cz

Figure 4: Expert list of Czech transparency organisations

Twitter

To illustrate different analytical approaches in TCAT, we used the example of a major announcement around UK government spending, the UK’s “Spending Review”. First a co-hashtag analysis was applied.

There were over 4,700 unique hashtags that had been used at least 3 times. These illustrate a wide range of different concerns and positions around public spending (with frequency of use designated in brackets after the hashtag). The most frequently used hashtags were the ones associated with the event – e.g. #SpendingReview (131636), #SR15 (90698), #AutumnStatement (13918), #SR2015 (3164). There were also hashtags reflecting publications and venues where discussions around the spending review were taking place, such as #PMQs (2975) – the BBC’s Prime Minister's Questions programme – and #Bbcdp (1651) – the BBC’s Daily Politics programme.

Others reflect topical concerns around public spending plans. For example the #saveesol (2117) hashtag was used for discussions around planned spending cuts to ESOL (English for Speakers of Other Languages) courses. The top shared link on this hashtag was a link to a public Facebook group called “Action for ESOL”. The #TamponTax (1969) hashtag was used to discuss plans around the so-called “Tampon Tax” (a 5% tax on sanitary products). Previously a petition of over 300,000 people argued that the tax should be abolished. An official announcement as part of the Spending Review stated that money from the tax would be donated to women’s charities. 1 This was met with a critical response from Twitter users, journalists and women’s charities. 2

The hashtags also reflect discussions and interventions regarding other public services and spending areas, including the following list. Further analysis using TCAT could tell us which users, URLs, and issues are associated with each. For example, the table below list the most common co-hashtags and could the starting point of such an analysis:
  • #mentalhealth (993)

  • #localgov (892)

  • #ukhousing (835)

  • #SocialCare (714)

  • #police (702)

  • #nursing (545)

  • #carecrisis (438)

  • #ukpoverty (405)

  • #housing (373)

  • #tax (328)

To see not just the frequency, but also the relations between these hashtags, Gephy was used to generate a tag cloud.

Figure 5: Tag Cloud for UK Spending Review 2015

There are other possible analyses besides co-hashtag. For example, we also examined the most common images or URLs in these tweets. Further possibilities will be explored in the follow up research.

Discussion

Digital methods are especially suitable to broaden known networks. The research found an additional invaluable characteristic: with the right preparation it allowed us to map a previously ‘unmappable’ audience, the temporary public. First we will describe the lessons learned by method.

Embarking on a new field usually start with a “quick google search”. The search engine results method lifts this to scientific standards by working with research browsers, looking at a large number of results and coding the results. It provided us with a solid overview of different types of information that one receives about the topics, the actors and institutions that disseminate the information and the different angles in the debates. We used technical search terms, and one general search term. The general term provided us mostly with media reports. The more technical terms with institutional actors. Surprisingly, the organisations and user-categories that were returned seemed to reflect political cultures of the countries studied. A finding that we certainly need to look into in follow up research. Most important however was that in comparison to the scoping and expert lists and interviews that were done previously, vastly different players showed up and transparency organisations were almost entirely absent for terms such as EU budget or ESIF.

The Hyperlink analysis crawls websites for all the outward links and in turn crawls these websites and links etc. This method relies heavily on the list of websites and URLs that are given as input. We first attempted to provide input from the search engine results, but this did not provide satisfactory results in terms of comprehensive networks and deeper analytics than we had made by manually coding the links. When compared this to the list from Czech, where our budget expert provided the list, we found that the tool did work in producing networks, but rendered little new actors or information that was not already known to the budget experts. We should first retest the tool, whether with a smaller list of a well-informed but not expert researcher such a network can also be produced. However, we might also attempt to find new tools that find links between organisations based on different characteristics than just hyperlinks, as this is not how websites are built up anymore.

Lexis Nexis is a paper- and media-collection used mostly in the Netherlands but with an extensive collection of European Newsletters in all languages. This research showed us that reporting around the EU budget is very event driven across different countries.

As a tool, however, one has to cross-check which newspapers are actually queried. Important newspapers as the Financial Times are for example not included. However, as a snapshot of what the “media” says about a certain event or topic, it serves well. For more specific topics, and finding everything that has been published, it does not suffice.

Twitter analysis seems a versatile and in depth method to map both publics and topics around budget and spending. Here we have to keep in mind that the public is limited to the twitter audience. In addition, the debate that one attempts to capture needs to have enough participants and be “large enough” in society to capture a wider audience - beyond the budget institutions and their direct stakeholders. For example, the spending review in the UK worked very well, but the EU budget debates are much less talked or tweeted about and thus do not give information about topics or wider publics.

In the continuance of our stakeholder identification, we will merge our current separated efforts in participatory methods and in digital methods to one joined approached. In this way, we will not only identify our current stakeholders, we will studying how to find new stakeholders as well. In the above, we have tested and listed “old” and “new” methods for identification of stakeholders.

One of the challenges to any stakeholder identification efforts in fiscal and financial transparency is that the wider public's interests in the financial side of politics and the public sphere are linked to specific topics. So the question is, how to identify these topics, reach out to these publics and broaden our field.

Bibliography

Gray, J. (2015). Open Budget Data: Mapping the Landscape. Available at SSRN.

Rogers, R. (2013). Mapping Public Web Space with the Issuecrawler. In B. Reber & C. Brossaud (Eds.),

Digital Cognitive Technologies (pp. 89–99). John Wiley & Sons, Inc. Retrieved from http://onlinelibrary.wiley.com/doi/10.1002/9781118599761.ch6/summary
Topic revision: r1 - 04 Mar 2016, DannyLämmerhirt
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