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A Blog recording the life a Web Scientist
Well, ICTD2012 is over, and what a great conference it has been! Loads to take away from it, there was really great energy there, which has been truly reflected in the Twitter conversations that developed over the past 4 days.
Following up from the previous post, I have examined the dynamics networks that formed as a result of the communications of twitter users (tweetees); these communications are either retweets (like the graphs shown in Part 1 of this blog post), or through users mentioning each other within their tweets.
Before we get to looking at the different communication networks that emerged, let’s examine the frequency of tweets during the conference. Over the 4 days, 2299 tweets were made, and out of those, 1437 of them were retweets, and out of the remaining tweets, 646 had mentions contained in them. That’s a good deal of communications between people! This can now be examined in a little more detail.
Slideshow 1 is of the Mention communications captured before and during the ICTD2012 conference:
Let’s first look at the evolution of the ‘mention’ network over the past 4 days. As the slideshow shows, there was a good amount of communications between users, this resulted in an average degree of 1.7 with a maximum in-degree of 33, which basically means each user was on average in communications with 1.7 (call it 2 people). Also, a little bit more analysis of the data revealed the top 10 users to be mentioned within the conference.
Slideshow 2 is of the retweet communications captured before and during the ICTD2012 conference:
Slideshow 3 shows the comparison between the unclassified and classified retweet network at Day4 of ICTD2012:
Examining the retweet network graph exposes the same kind of activity, over the 4 days, the number of retweets between users was phenomenal, with an average in degree of 3, and a maximum in-degree of 49, and a maximum out-degree (number of times a user retweeted other unique users) of 47. Putting this into context, this means that there was a lot of sharing of information (but was it valuable…) between users, and some users were showing signs of being Hubs (users retweeting many other users) and authorities (users being highly retweeted by other users). As with the previous post, I applied the classification model on top of the data set, setting the minimum number of retweets to be a red node (an authority) to 40 (same as part 1). At the end of day 4, we are now seeing the addition of one red node (@anahi_ayala) and a load more yellow nodes connecting these users together; however ranking these yellow nodes based upon the number of times that they were the first ones to retweet a tweet that got retweeted multiple times (which results in the size of the yellow nodes), @melodyrclark and @shikohtwit came up top.