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This is a thread by @Shobz on twitter analyzing those behind the anti-dam Twitter campaign. Link to the thread at the end of this analysis.
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I am looking at the social network graph for the dam hashtag. It's a cluster which indicates a lot of coordinated activity.
I was able to get as much data as Twitter permitted. There are two things I did. One was to do a very basic analysis and the other was to make a map/graph of the hashtag. Due to Twitter image size restrictions, I am unable to show the finished graphs/maps.
Let's start off with those who populated the trend with their tweets. Look at the volume of tweets being sent.
Here is a graph of those with a large number of followers. Some of these names should ring a bell. You can tell a lot about the affiliation of the first one on the list.
A bulk of the tweets from this dataset did not get any RTs. Then there are around 4425 which got less than 5 RTs.
The follower count is also quite interesting. Many accounts which barely have followers.
Now I am going to share some of the repetitive tweets.
Exhibit A:
Exhibit B:
Exhibit C:
Exhibit D:
Exhibit E: There was a long list of tweets so I just showed a few. The image URL differs but that's alright as it's not unique.
This is an overview of the hashtag as displayed as a network. The colours indicate the clusters/communities. Notice how some are close together, while there are others who are distant.
Another view of the network. You can see the various clusters/communities.
I filtered the network so it would be possible to see some of the labels for these nodes. If you look below you can see @KhurramDehwar at a distance. This was due to his contribution in debunking the lies being spewed by the Anti-Dam crowd.
There is a lot more but this should suffice. It is certain that there are a lot of PPP supporters and others who are working on this hashtag.
There are others who are also involved in this hashtag but they are further away from the main nodes in the graph. Some of it is visible, while others aren't. There are a lot of strongly connected nodes there with some which have no connection.
For those who don't understand what clusters are:
They are basically people who are close to each other/now each other well and have retweeted each other a lot.
A simpler explanation:
Cluster:"a group of similar things or people positioned or occurring closely together."
A lot of these handles with a low follower count don't show up in the filtered graph. I have used parameters to show nodes with a certain value. That does not include a lot of the accounts which were used to populate the trend.
==============
I am looking at the social network graph for the dam hashtag. It's a cluster which indicates a lot of coordinated activity.
I was able to get as much data as Twitter permitted. There are two things I did. One was to do a very basic analysis and the other was to make a map/graph of the hashtag. Due to Twitter image size restrictions, I am unable to show the finished graphs/maps.
Let's start off with those who populated the trend with their tweets. Look at the volume of tweets being sent.
Here is a graph of those with a large number of followers. Some of these names should ring a bell. You can tell a lot about the affiliation of the first one on the list.
A bulk of the tweets from this dataset did not get any RTs. Then there are around 4425 which got less than 5 RTs.
The follower count is also quite interesting. Many accounts which barely have followers.
Now I am going to share some of the repetitive tweets.
Exhibit A:
Exhibit B:
Exhibit C:
Exhibit D:
Exhibit E: There was a long list of tweets so I just showed a few. The image URL differs but that's alright as it's not unique.
This is an overview of the hashtag as displayed as a network. The colours indicate the clusters/communities. Notice how some are close together, while there are others who are distant.
Another view of the network. You can see the various clusters/communities.
I filtered the network so it would be possible to see some of the labels for these nodes. If you look below you can see @KhurramDehwar at a distance. This was due to his contribution in debunking the lies being spewed by the Anti-Dam crowd.
There is a lot more but this should suffice. It is certain that there are a lot of PPP supporters and others who are working on this hashtag.
There are others who are also involved in this hashtag but they are further away from the main nodes in the graph. Some of it is visible, while others aren't. There are a lot of strongly connected nodes there with some which have no connection.
For those who don't understand what clusters are:
They are basically people who are close to each other/now each other well and have retweeted each other a lot.
A simpler explanation:
Cluster:"a group of similar things or people positioned or occurring closely together."
A lot of these handles with a low follower count don't show up in the filtered graph. I have used parameters to show nodes with a certain value. That does not include a lot of the accounts which were used to populate the trend.