Dear all, here is a short outline on the preparation of the Paris Sprint.

• Dates & Venue

Jan 6th to 10th, at Sciences Po, Paris. We have pre-booked rooms in a nearby hotel.

• Programme

Under deverlopment.

The first morning will be dedicated to presentations by alpha-users. Then, we will form interdisciplinary teams of 5/6 people constituted of EMAPS members + friends.

• Topic

• Alpha-users

• Other participants

EMAPS members : I already got some answers. Here is the form which you are invited to fill in to confirm your participation ASAP (and before the end of the week) :

https://docs.google.com/forms/d/1Q58PtYxvJRHYHitSX47lnuKu00CVfMmC7lFv617n598/edit

EMAPS members are encouraged to stay the whole duration of the Sprint.

Advisors : we have sent an invitation to Pelle Ehn and David Chavalarias.

Students : we plan to have 3 Density Design former students.

Issue experts : we want to have experts of the climate controversy (apart from Mark who will be there as well) like Amy Dahan & Christophe Buffet (Centre Alexandre Koyré), Clive Hamilton, Alice Caravani of Climate Funds Update (Overseas Development Institute). François Gemenne will moderate the presentations by alpha-users on the first morning.

• Expenses

All expenses including transportation will be borne by Sciences Po. We will book hotel rooms, but we ask EMAPS participants to take care of their own travel, which will be reimbursed after the sprint.

Entitled “You are not the API I used to know: On the challenges of studying social media data”, the 7th annual DMI Summer School took place from 24th June to 5th July 2013 at the University of Amsterdam. This year’s Summer School generated tremendous interest and the turnout has never been this high. Participants attended lectures and workshops from experts in social media data and mapping, and conducted a variety of research projects.

One larger research project conducted at the DMI Summer School was dedicated to the mapping of climate change. The aim of this project was to explore the uptake of climate change issues across platforms and over time. The platforms included in this study were: the Google search engine, Google Trends, Twitter and Amazon. We asked: are there different discourses in the climate change issue space across platforms? Are these time-specific? Geo-specific? Platform-specific? User(type)-specific?

As a starting point for the cross-platform research first a list of keywords associated with each of the three approaches (scepticism, mitigation and adaptation) was build. This was done in a rather experimental but effective way, namely by means of the Amazon Book Explorer tool. As search terms, the three approaches to climate change (scepticism, mitigation and adaptation) were queried. As a result, the tool output the most popular books associated with the terms and any relevant metadata about them. From the book titles the researchers manually captured keywords, which were later cleaned and compiled into three different lists.

After compiling the three lists of keywords, their uptake in the different platforms was analysed. By means of the DMI tool TCAT (Twitter Capture and Analysis Tool), Twitter was queried for the presence of each of the keywords over a period of 7 months, as well as Google.com for a period of 10 years by using the Wayback Machine. For the platform Twitter it was also of interest which clusters can be identified within tweets on climate change, which resulted in a co-hashtag map (figure 1). This revealed that some geo-locations appeared to dominate the discourse, such as Australia and US (politics, flood and drought), and Canada (flood). Interestingly, the top clusters do not particularly match vocabularies of scepticism, mitigation and adaptation. Further, it was examined who the users of these hashtags are, and if certain hashtags relate to specific events. We found political polarisation among the users of conservative and progressive hashtags within the cluster around the Obama speech on climate change.

Figure 1: Twitter hashtag clusters around the hashtag global warming/climate change. Depicted as network graph. The visualization reveals clusters around geolocations such as Australia and US (politics, flood and drought), and Canada (flood), with each color representing a different cluster. Source: Hashtags associated with the queries [global warming], [globalwarming], [climate], [climatechange], [drought], [flood], collected through the DMI Twitter Capture and Analysis Tool (TCAT). Queries performed between Nov. 2012 – June 2013.

The sub-project on climate change popular language uptake on Amazon is another interesting project, as Amazon is approached and repurposed as a research engine rather than a mere online retailer of books. Here the question is what sub-issues in the climate change debate sell best over time and how the uptake of the different sub-areas of climate change (scepticism, mitigation and adaptation) evolves over time in the mainstream literature. For scepticism most of the successful language emphasizes the scandalous and urgent nature of deception, such as: “corruption”, “conspiracy” and “hoax”. The keywords or sub-issues captured for mitigation and adaptation are clustered around shared terms, even though they obey a different logic. When seen in a (issue) timeline (figure 2), it appears that popularity for mitigation and adaptation centers around more recent published books, while best selling books in the realm of scepticism is composed of both older and newer titles. This indicates that keywords used on the subject of climate change scepticism in mainstream literature remained relevant over the years. As for popularity, the analysis on Amazon’s query autocomplete system revealed that adaptation and several keywords associated with scepticism are suggested while mitigation is not, perhaps indicating a less popular or effective terminology.

Figure 2: Climate change formats and keyword uptake. Depicted as bubble matrix. The visualization includes on the right side the keywords captured from book titles, and below the year that corresponds to each of the books from which the keywords were captured. Every approach to climate change (adaptation, mitigation and skepticism) is depicted with a different color, allowing to identify overlapping and repetition amongst keywords. Source: best sellers books in Amazon.com associated with the queries [climate change mitigation], [climate change adaptation] and [climate change skepticism]. Queries performed on 30 June 2013.

This last project has caught our interest on how Amazon can further be repurposed as a research engine as a means to map issues.

Since February of this year we have been running the second version of the Issue Mapping for Politics course where students have engaged in climate change controversy mapping through three periods of the controversy: (1) the very existence of climate change, skepticism and causes, (2) mitigation (quantified self approach and carbon market approach), and (3) adaptation. Climate change issue experts have been involved in each of these stages. More precisely, they were invited to describe and present the state of affairs of their fields and tell us about their analytical needs. Based on these presentations students were asked to produce maps. Afterwards, we will organise a follow up with the issue experts to present them with the maps, and engage with them concerning the extent to which they meet their needs, including any new needs that arise from reading the maps.

During the EMAPS meeting last month, the University of Amsterdam presented field notes from our work with these climate change issue experts. Below is a summary of some of the most relevant things we learned from them, which we consider could be useful to other project members working with issue experts. The slides from our talk can be found here:

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This blog post is a response to Axel’s post asking each partner to rethink their work according to the new strategy discussed in the project meeting back in December. It details the work that the University of Amsterdam will be conducting in this second year of the project.

Over a period of 16 weeks, which started in the first week of February,  the University of Amsterdam will be running the Issue Mapping for Politics course. The course takes students through four different mapping methodologies and theories: controversy mapping in the style of Bruno Latour and Tomasso Venturini, risk cartography using Ulrich Beck’s theories about global risks, critical and neo-cartography using Jeremy Crampton guidelines on the subject, and finally issue mapping techniques developed at the University of Amsterdam.

Students are encouraged to apply these methods and theories on mapping climate change. We are aiming to study climate change controversies through three periods: (1) climate change existence, skepticism and causes, (2) mitigation (personal approach and market approach), and (3) adaptation. This practical part of the course is where the University of Amsterdam will be implementing the new project strategy discussed in December. In each class we are inviting one issue expert: one climate change skepticism expert, one carbon trader, one carbon footprint quant, and one city auditor to talk to students about their work in these areas and about their mapping needs. The students are invited to produce maps and visualisations in response to these discussions with climate change experts. In parallel we will connect with the Guardian Datablog and other media organisations in order to understand mapping needs of yet another important category of users, and aim to collaboratively produce maps and visualisations that are of interest to the Datablog and other publications.

In terms of the project plan and description of work, there is one main change that we anticipate. According to the Gantt chart, in the second year of the project, the main contributions that the University of Amsterdam brings are the release of D1.2 “Recommendations and guidelines for the project” in March, which will consist of the ageing book, now in its final stages of production, and the work under work package 4, “Platform development and community building.” The UvA can include the engagement with expert users and production of climate change maps and visualisations in this work package. In this case, the starting date of the work package, which is now the second half of the year, would need to be changed to February 2013. The outcome of the work will be documented on the EMAPS platform and included in one of the final deliverables, due in the last month of the project.

On December 12 2012, the EMAPS project organized its first Issue Safari.
Such workshop was an improved version of the seminar we organized in June 2012. In both cases the objective was to submit some of a set of maps we had prepared on the theme of aging in UK to the evaluation of a selected group of potential users.
The first workshop had been very interesting, but had also revealed the great difficulty of finding a common ground between mappers and users. Users were very critical on several aspects: from the choice of the research questions, to the datased employed, from the visualisations employed to the legibility of the maps (see emapsproject.com/blog/archives/1329).
In order to overcome this difficulty, we started a new process of interaction with the users (described here emapsproject.com/blog/archives/1701, here emapsproject.com/blog/archives/1728 and here emapsproject.com/blog/archives/1754). This process helped us to produce a more effective set of maps and to identify a groups of users potentially more interested in our visualisations. The December Issue Safari was the result of this process.

I think it is fair to say that the Issue Safari has been a success in the sense that we have greatly improved the adaptation between users and maps. Most users found most maps relevant and engaged with them in interesting ways. This allowed us to collect a richer user-feedback that we will now be able to re-invest in the case study of climate change adaptation.

Drawing on a very detailed set of notes collected during the Safari by the facilitator of the Young Foundation and compiled by Lucy Kimbell, I have prepared the following synthesis of the lessons we learnt during this workshop

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In a recent study, we analysed the interactions between self-proclaimed Democrats and Repubblicans in Wikipedia.

We started from the identification of users having in their personal page a userbox indicating support for one of the two major US parties. In this way, we were able to identify about 800 Democrats and 600 Republicans.

This allowed us to study representation practices, activity and interactions of these two sets of users according to several dimensions, such as the kind of the other userboxes they had in their profile, the articles most edited by each party, the presence of conflict in the threads in which they were involved, and the emotional content of their messages.

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Ahead of our two-day workshop in London later this week, I present some suggestions that follow on from our discussions in the project team about we can engage productively with people who might use the issue maps we are creating in the project. As I understand it, the role of The Young Foundation in the EMAPS project is primarily about helping to engage with people beyond the project team, specifically with the communities of issue professionals working on the two topics.

This post builds on recent emails and skype meetings between us; our small workshop in Oxford in October (see posts by Michele and Benedetta in Milano and by me afterwards, with comments by other EMAPS team members), as well as our June meeting in London (see posts by Tommaso) and discussions about the design process by Milano and Paris.

I will cover

• a narrative about the project’s trajectory to date in terms of engaging with issue professionals, written from a personal perspective as someone working within YF on EMAPs since March 2012 (when I was employed there, and now freelance);
• a brief introduction to some concepts and methods from the fields of Participatory Design and Design Research, which offer some approaches that could move EMAPS towards a more participatory mode of designing/using maps in the context of a research project;
• a speculative description of what these concepts and methods might look like in practice, if the EMAPS team decided to use them.

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We have recently started to work with an interesting additional data-source for Wikipedia data: the number of views per hour a specific Wikipedia page receives. This data is available at this website http://dumps.wikimedia.org/other/pagecounts-raw/ and contains view data since 2008.

Below we present three examples of the temporal evolution in  the interest a specific Wikipedia article generates. Until now we have extracted and processed view data from 2008 till March 2010, more data is being currently downloaded.

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In this post we have drawn the network of hyperlinks connecting Wikipedia articles related to climate change. Now we will focus on how to identify the most central articles in the network.

Applying different metrics we can study which issues are more central within our set of articles according to different criteria:

• In/Out-degree: number of incoming/outgoing links. It measure centrality as the number of connections with other nodes.
• Pagerank: like in-degree, but the weight of each incoming connection depends on the importance of the corresponding node; weights are computed iteratively. It can be seen as the probability of reaching a node when following a random walk in the graph.
• Betweenness: number of shortest paths from all vertices to all others that pass through the given node (i.e.: how often the given node lies on the shortest path between a pair of nodes). It quantifies the importance of a node as a bridge between different nodes or groups in the network.
• Closeness: Average distance from a node to all the other nodes in the network. It represents centrality as the ability to reach the other nodes in few steps.

On October 12, we met in London Maria Parsons, Margaret Melling from MM Consulting, Penny Thewlis and Diana Roberts from Age UK. The meeting was mediated by our Young Foundation partners Lucy Kimbell and Kat Jurgnickel.

Our aim was to have feedback from a group of users playing an important role in the Ageing controversy, in order to get a consistent assessment on the analyzed data and on the graphic solutions of the latest visualizations.

The visualizations were based on a dataset provided by Sciences Po and aimed to answer three questions decided together with Young Foundation and Maria Parsons:

1. What is living well with dementia?
2. What are the public health and social care messages about ageing and dementia?
3. Are older people assets or deficits?
Each issue had been studied by Sciences Po in order to focus better on data available on the net, through digital methods, and formulate more specific questions.

Q1: What is living well with dementia?
a-Which online resources aim at helping people to live well with dementia?

The first set of data was built with the aim to understand which resources are available online to help older people with dementia. Sciences Po selected then a list of dementia-related blogs run by elderly people living in UK.

This first visualization shows the links between these blogs.

PROS: Users demonstrated a certain interest in this map because it highlights the connections and relationships between blogs, which wouldn’t be immediately understandable while netsurfing.

CONS: Unrelated blogs were presented as a separated list, which was interpreted as a legend at first.

As a second step we showed the same set of data spatialized with Gephi.

PROS: Most of the users expressed a preference for this visualization because it emphasizes clusters while connections are easier to read compared to the first graphic solution.
CONS: One of the users remarked that this type of representation looks chaotic and complicated; she compared it to a spider web.

In the following step the blogs in the corpus have been crawled in order to build a second, wider network. Since the results of the crawl were not yet available, we built a sample dataset and used it to develop different visualizations.

It was very difficult for the users to focus on the visualization since they knew it was built on a sample dataset, so we were able to get just a few feedbacks:
- Table 1: ”There is too much data, it would be better to remove the connections between the blogs already showed in the first visualization.”
- Table 2 (tree map): This kind of representation isn’t easy to understand for those who had never seen it, while those who could already read it, aren’t able to compare the areas size.

Q2: What are the public health and social care messages about ageing and dementia?
a- Which linguistic expressions are most frequently used by public health and social care institutions when talking about aging and dementia?

This visualization shows a bipartite network between documents and keywords. It’s the result of a semantic analysis of Ageing and Dementia related documents provided by the Young Foundation.
The visualization highlights the most important keywords and their links to the documents.

PROS: Users seem very interested in the network, although they didn’t immediately understand it. However the visualization could potentially be useful. Thanks to the mediation of Mrs. Parsons, the other users were able to find the clusters and to explain us the closeness of some keywords to the documents.
They also suggested to create a similar visualization to show the evolution of blogs and websites over the course of time and to build interactive visualizations to favour the exploration of the data.

CONS:
- At a first glance they couldn’t understand the difference between a network and a tagcloud. One of the users referred to as the biggest node of the network as a“big centre of something”, without understanding the structure of the visualization she was watching.

- They didn’t understand the spatialization made with Gephi, they erroneously thought that only the documents and the keywords in the center of the network were important.

- They tried to follow the links but they expressed some confusion.
-They were confused by the use of the same node shape for documents and keywords

On the basis of their feedback we think it would be useful to create a guided exploration of the maps, helping users to read them. One possible solution could be to create some overlapping levels that explain the data collection process and the creation of the network.

Q3: Are older people assets or deficits?
a- In different European web-spheres, which images are used to picture older people?

This third set of visualizations aims to show the results of a search on Google Images. The data were collected from Sciences Po, using “Old Age” as a query translated into various languages and searched in the different national domains of Google.
The images obtained were classified according to two criteria:
- Older people portrayed as active and healthy / Older people portrayed as ill or in need
- Ageing portrayed as an enjoyable period of life / Ageing portrayed as suffering

PROS: They thought it’s useful to understand how people with dementia are represented and it could be useful also related to other media.

CONS: -They expressed their interest for the visualization, but they didn’t look carefully at the pictures or compare the results in different countries.
They showed some difficulty in understanding the importance of this set of data in relation to their work and they couldn’t tell if the classification made sense.

Conclusions
Users were very fascinated by the possibility to obtain data from the web, to create relations and visualize them, making information accessible to the public.

We noticed that users were interested in the data only when they were explicitly involved or represented in the visualizations.

One of the users underlined the importance to promote a collaboration between the stakeholders, and to create a dialogue between who collects the data and the final users to make visualizations answering their needs.

This experience remarked that the only way to understand the real effectiveness of the diagrams is to observe users interacting with them, while direct questions about the meaningfulness of the maps don’t lead to a reliable feedback.