[Dataset] Analysis of ego-networks of two CS-related Twitter accounts

<strong>Explanation/Overview:</strong> This is the dataset for the analyses and results on Twitter Ego-Networks of two CS-related accounts (@EuCitSci &amp; @SciStarter). The username have been anonymised. <strong>Purpose:</strong> The purpose of this dataset is to provide the basis to reproduce the results reported in the associated deliverable. As such, it <strong>does not</strong> represent <strong>raw data</strong>, but rather files that already include certain analysis steps (like calculated degrees or other SNA-related measures), ready for analysis, visualisation and interpretation with R or any other network visualisation software (e.g., Gephi). The edges represent the follow relation and were retrieved using the Twitter API. All usernames except those of the two ego-accounts were anonymised by assigning a random number to each node. Due to the size of the network, we do not include any <code>.gexf </code>or <code>.gml </code>files in this upload, but rather resort to node and edge lists in the <code>.json</code> format <strong>Relatedness:</strong> The networks are the ego-networks for two related public accounts that are associated with citizen science (@EuCitSci &amp; @SciStarter). <strong>Content:</strong> In this Zenodo entry, two files can be found. <code>edges.json</code> Represents the edge list, with the columns: <code>source</code> <code>target</code> <code>wherefrom</code> <code>account</code> EuCitSci 23929 friendslist EuCitSci <code>Source</code> and <code>target</code> are the necessary columns for the network creation and in this example indicate that EuCitSci follows 23929. <code>wherefrom </code>indicates the origin of this relation in the crawling (i.e., whether it was retrieved using the friends or follower list) and <code>account </code>indicates the ego-account it belongs to. Thus, the edges can also be separated using this <code>account </code>attribute as they represent two distinct networks. <code>nodes.json</code> Represents the nodes in the networks. The following data fields are contained: <code>username</code> <code>CS</code> <code>followers_count</code> <code>friends_count</code> ... 1116 CS 689 514 ... ... <code>favourites_count</code> <code>listed_count</code> <code>statuses_count</code> ... ... 2601 18 2141 ... ... <code>degree</code> <code>in_degree</code> <code>out_degree</code> ... ... 21 5 16 ... ... <code>reciprocity</code> <code>account</code> ... 0.48 EuCitSci <code>Username </code>represents the numerical and anonymised username, <code>CS</code> the community-membership. The different counts (e.g., <code>followers_count</code>) indicate the number of followers the user had at the time of the retrieval by the Twitter API. <code>degree</code> refers to the degree in the network (similarly the <code>in-</code> and <code>out_degree</code>), while <code>reciprocity</code> refers to the number of mutual edges in respect to the total number of edges per node (see here). <code>Account</code> is similar as described above. <strong>Grouping:</strong> The data is grouped according the ego-account it is associated to, as can be read above (i.e., the <code>account</code> attribute).