Blog 2 – Gephi

The data shown in the graphs are from the hashtag #ps5ukstock from the Twitter trending page. This hashtag was trending because Argos had restocked the Play station 5 at 3 am, which led to customers being annoyed as they did not manage to purchase one of the Playstations that were in stock by the time that they woke up.

The size of the nodes depends on its degree of centrality. The centrality measures are an essential metric to help analyse the position of a node in a network (Grandjean, 2015). There are two types of centrality: betweenness and closeness. Betweenness looks at the number of shortest paths that pass through a node divided by the total number of shortest paths between any two nodes in the graph.  The largest node has the highest degree, whereas the smallest node has the lowest degree. The colour of the nodes represents how connected they are. In the graph shown below the darkest node shows that it has a high value, therefore being highly connected. Additionally, the lighter nodes have fewer connections meaning they are of a lesser value.

The nodes represent the users that have tweeted this hashtag. The size and colour of nodes show the degree of the node (the number of edges connected to the node) and how connected the user is. One of the graphs shows the name of the user on the node. Depending on the size of the node, it tells us how connected the user is to others. In this case, the user called @voiceofreeveson has the largest node telling us that they have the most connections on Twitter out of the rest of the users that the data collected.

Two of the light green nodes have thick arrows pointing out of them as their edges. The thicker edges have a larger weight because this is the number of tweets that the user has tweeted with this hashtag. In addition to this, the thicker edges in the graphs show that they are directed connections as they are in arrow form, whereas the rest of the nodes have an indirect connection. The light green node has an out-degree of 2 as the edges are going away from the node. It also has an indirect connection to another node. This tells us that this user may have an influence over two different users that are not in their close network and what they may tweet/respond too. It also tells us that they have a direct connection with another user that may see their tweet and be in their close network.

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