# An Approach to Exploring Non-Governmental Development Organizations Interest Groups on Facebook
## 2 Methodology
### The Process of SNA on the Organizations' Facebook under Study
(2016) [55] is of interest, who found that small-scale SNA in social networks reveals valuable information about relationship management for nonprofit service organizations. Moreover, [PERSON] et al. (2018) [75] conducted a study to examine the social media strategies of three cruise lines over three years, analyzing the network structures on Facebook and Twitter and demonstrating the value of the STAR (storytelling, triggers, amusement, and reaction) model for improving social media activities. In culture, [PERSON] (2017) [58] developed a study on the usefulness of [PERSON]'s social theory in digital social network research. To this end, he conducted a case study focused on the Royal Dramatic Theatre in Sweden, whereby he found that a network analysis of a group of institutions in social networks can begin to uncover the breadth or scope of a social field, which, according to the author, is rare in empirical field research. 3. Selection of the social network. The choice of Facebook was motivated by its high social impact, affordability, and ability to generate interactive communication, which are elements that foster relationships with non-profit organizations [76]. It is the social network most used by NGDOs, as discussed in Section 1.1, corresponding to the importance of digital social networks in the NGDOs context. 4. Data extraction. The Netvizz v1.44 module called the \"page like network\" allows data to be extracted from Facebook, which creates a network of pages connected by the \"like\" action [77]. The \"like\" of an official Facebook page is more durable than the like of a post since it is not linked to a specific publication that appears at a particular time but is attached to the page in question (in the section \"like\" this page). In addition, when the person in charge decides which institutions to \"like\" on Facebook, he does so on behalf of the organization he represents, so it does not have the same meaning that the likes of a publication may have. The publications' likes can be ironic, humorous, and even modeling [78]. The likes of Facebook pages are a symbol of recognition [58]. The crawl was conducted on March 2019 and generated a total of 46 nodes (Facebook pages) and 291 edges (connections, in the form of \"likes,\" between the pages) in the RCC's Facebook, and 84 nodes and 775 edges in CAJ's Facebook. 5. Selection of the metrics. To respond to each of the objectives set out in point 1 of this process, the following metrics were used: diameter of the network, average path length, modularity, degree centrality, out-degree, in-degree, and intermediation centrality. These metrics, together with the objectives for which they are used, are explained in Table 2.  
Regarding modularity, it is necessary to indicate that the Leuven modularity algorithm, a method widely used in the literature and applicable to the field of social networks [83], was used to identify the different communities within the networks. The basic idea was to look for regions within the graph where the interconnections between the nodes were relatively dense compared to others in the network. In other words, the modularity of a partition is a scalar value between -1 and 1 that measures the density of links inside communities as compared to links between communities. This value can be represented numerically:  
\[M=\frac{1}{2m}\ \sum_{ij}\biggl{[}A_{ij}-\ \frac{k_{i}k_{j}}{2m}\biggr{]} \delta\left(c_{i},c_{j}\right)\]  
where \(A_{ij}\) represents the weight of the edge between \(i\) and \(j\); \(K_{i}\) is the sum of the weights of the edges attached to vertex \(i\); \(c_{i}\) is the community to which vertex \(i\) is assigned, and  
\[m=\sum_{j}A_{ij,.}\]  
The degree centrality, which corresponds to the number of links that a node has with the others, can be re-stated by the following formula [84]. \[C_{DEG}(j)=\sum a_{ij}\]  
Position _aij_ assumes the value of 1 if the edge (\(i\),\(j\)) exists and 0, if it does not.