Just sharing stuff…
The plots below show the Mention Network of Twitter users (bots and humans) discussing the Philippine Elections. Building a network such as the ones here can help one to visualize (and even reveal) relationship patterns that aren’t too easy to see—such as unveiling who’s always talking to whom—could be bot to bot using certain specific hashtags to jack up the volume of tweets on a candidate.
In the mention networks below, the nodes are the users while the edges represent mentions. For example, if Twitter user i mentions Twitter user j in a tweet on the Philippine elections, a directed link (i, j) is drawn between them. Note, too, the node sizes. The bigger a node is means that the more his/her name is mentioned in the tweets. Now, whether or not the tweets are positive or negative—it’s not covered in this blogpost.
The first plot (above) shows a complete picture of the dataset collected, while the second (below) shows the largest cluster. For the first two plots, I used Python for plotting using the graph-tool package. For the third one, I used Gephi; I find it easier to add the node labels on Gephi. Also, in the third mention network, the nodes are colored by community.