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--- wiki:stakeh_as_network_analysis [2014/12/13 14:49] – dominikcs
+++ wiki:stakeh_as_network_analysis [2014/12/13 14:54] (current) – dominikcs
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-==== Stakeholder network analysis ====
+==== Stakeholder network analysis====
 Data on project participation of the stakeholders has also been used to analyse the stakeholder network behind the AS projects. For this, we have used social network graphs. These graphs are visual tools that enable us to explore proximity, relationships and their strengths between stakeholders, here the Alpine Space project partners. They have their foundation in social network analysis (see Hanneman and Riddle (2005) for an introduction) which is based on mathematical tools and graph theory. By definition, a social network is simply a set of actors (nodes), that may have relationships (edges) with one another. In our case, the network nodes are all identified stake holding institutions in the 30 AS projects along the 2007-2013 programming period. The list of stakeholders was created using the excel sheet from the JTS. However, this list might be subject to bias as different practices exist in declaring project partners, especially for large institutions such as regions, provinces, universities or research centres (head institution, sub-units). Therefore, and contrary to the main stakeholder analysis, we derived a second dataset by aggregating stakeholders according to their head institutions. In the aggregated dataset, the number of stakeholders dropped from 231 to 189, i.e. 40 institutions are in fact sub-units of head institutions. This generalization gives us insights on the real importance of these head institutions; information that is not available in the disaggregated data. This consideration has consequences for the network graph. The edges are based on the collaborations with other stakeholders that took place during the projects. We do not consider variations in collaboration intensity (e.g. different intensities of collaboration in general, timely variation) as we did not have available such qualitative data. Although data might not appear rich on first sight (lack of intensity), the resulting graphs provide us with valuable insights on the (partial, only 28 projects) network established in the framework of the AS programme.
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 {{ :wiki:sl_final_acr_lps.jpg?direct&300 | Figure 2: Distribution of lead partners in the network, click to enlarge}} {{ :wiki:sl_final_acr_countries.jpg?direct&300 |Figure 3: Distribution of countries in the network, click to enlarge}}\\
-Finally, figure 6 shows the same network graph, but with node labels showing project affiliation for stakeholders with only one project and number of projects for stakeholders that participated in more than one project. In addition, node colours reflect the affiliation to clusters. These clusters have been calculated using the Chinese Whispers algorithm, a very basic algorithm that aims at "finding groups of nodes that broadcast the same message to their neighbours" (Biemann, 2006). With regard to the projects, we see that the social network graph positions stakeholders based on the links established by the thematically-related projects. For instance, partners in the project groups ACCESS, MORECO, demochange (territorial and demographic development), RURBANCE, CAPACITIES, COMUNIS (territorial and economic development), INNOCITE, SPHERA, ACCESS, NATHCARE (economic development) and MANFRED, ECONNECT, rechargegreen (environment) are situated close to each other.
+Finally, figure 4 shows the same network graph, but with node labels showing project affiliation for stakeholders with only one project and number of projects for stakeholders that participated in more than one project. In addition, node colours reflect the affiliation to clusters. These clusters have been calculated using the Chinese Whispers algorithm, a very basic algorithm that aims at "finding groups of nodes that broadcast the same message to their neighbours" (Biemann, 2006). With regard to the projects, we see that the social network graph positions stakeholders based on the links established by the thematically-related projects. For instance, partners in the project groups ACCESS, MORECO, demochange (territorial and demographic development), RURBANCE, CAPACITIES, COMUNIS (territorial and economic development), INNOCITE, SPHERA, ACCESS, NATHCARE (economic development) and MANFRED, ECONNECT, rechargegreen (environment) are situated close to each other.
-The partition of nodes using the clustering approach pushes this idea of grouping even further. It identifies nine clusters in our network, which correspond to the project affiliation of stakeholders and also to the degree of implication. There is a large central cluster (light blue) that collects all stakeholders that make up the "core" of the stakeholder network. It includes the partners that participated often in AS projects, and their competences might touch various subjects (links to the peripheral actors and their projects.\\
+The partition of nodes using the clustering approach pushes this idea of grouping even further. It identifies nine clusters in our network, which correspond to the project affiliation of stakeholders and also to the degree of implication. There is a large central cluster (light blue) that collects all stakeholders that make up the "core" of the stakeholder network. It includes the partners that participated often in AS projects, and their competences might touch various subjects (links to the peripheral actors and their projects. Other clusters confirm the grouping according to project themes in this graph. The red cluster highlights stakeholders working on environmental topics, the light green cluster those working on economic and territorial development topics; dark green is on construction, dark red is on geology, and dark blue also refers to territorial development.\\
 {{ :wiki:sl_final_acr_clusters_names.jpg?direct&300 |Figure 4, click to enlarge}}\\
+=== Interpretation ===
+In a nutshell, the stakeholder network analysis has provided some additional information on the relationships between stakeholders, which have been established throughout the 30 analysed AS projects. A central network of stakeholders has emerged whose members frequently participate in projects, thereby drawing other, more peripheral stakeholders into the network. Their collaboration (proximity) seems not be constrained by specific thematic focuses, but is probably based on a general interest in the Alpine Space programme (and funding) and in topics related to the Alps. These are the "hot hubs" of the programme. This group is completed by the lead partners, which can but may not be that central. We saw also that a distinction between stakeholders on sub-unit and main unit level does not result in the same network. In this regard, it seems essential to know how strong sub-units of institutions, participating in different projects, exchange information (administrative, project management, or thematic) and can be seen as stakeholders on their own. Information flow between sub-units might vary according to stakeholder types (authority, research centre, university). Finally, the cluster approach has pointed at the presence of some thematic sub-networks, for instance environmental or territorial development issues. Partners, once involved in a project, might explore new pathways and prepare follow-up projects on similar topics, thereby strengthening their links over time and overcoming limits of project duration. In this regard, the Alpine Space programme creates added value through networking.
 === Sources ===
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   * Levallois, C. (2014): [[http://www.clementlevallois.net/gephi/tuto/en/gephi_advanced%20functions_en.pdf|Gephi - Advanced functions. Filters, metrics, plugins and workspaces]]. Gephi Support Team, Lyon Business School.
   * Biemann, C. (2006): [[http://wortschatz.uni-leipzig.de/~cbiemann/pub/2006/BiemannTextGraph06.pdf|Chinese Whispers - an Efficient Graph Clustering Algorithm and its Application to Natural Language Processing Problems]]. Proceedings of the HLT-NAACL-06 Workshop on Textgraphs-06, New York, USA.
+//Dominik Cremer-Schulte, [[wiki:irstea|Irstea Grenoble]], December 2014//