This is a project that I am currently working on with David McDonald and Daisy Yoo, they are both from the iSchool. The project started last year (2012) and the main objective of the project was to understand the role of Twitter in the ongoing conflict in Syria. Moreover, we were aiming on understanding how people use the retweet function to amplify their voices during protracted political conflicts such as war. In this study, we use two metrics to measure influence: (1) content influence — the number of retweets that a piece of content is receiving; and (2) account influence — the number of retweets that an account is receiving.
That said, we had an initial hypothesis about the types of influential voices on the RT network: (a) activists, people with an idea or a cause, who have high content influence but low account influence; and (b) celebrities, who have both high content influence and high account influence. Furthermore, we assumed that activists’ influence would be based on proactive networking ability (two-way communication) while celebrities’ influence would be based on individual fame and authority (one-way communication).
However, the findings from our data reveled other interesting findings that neither of our hypotheses explained. For example, the image below is a network analysis of all retweets (From our dataset 1) November 10, 2012 – Syrian National Council Election, and in the image you will notice that there are nodes with high centrality and low centrality on the left of the digram. You will also notice that the edges have varied thickness, compared to the right small cluster (Purple color) . The right cluster looks like they were RTing each other equally and not only on this date, but in many others.
To know more about the right cluster and what were they tweeting, please stay tuned for the next blog post where I am going to explain what we found and our next steps.
1: Preparing the Dataset will be discussed in the coming post