bigdata – Norah Abokhodair

I spent some time reading the article The Rise of Twitter Bots published in the New Yorker. I very much recommend reading it if the word BotNet is new to you. The author – Bob Dubbin – spends sometime briefing the reader on what Twitter bots are and includes some anecdotes on different twitter bots and how they were developed ( This is especially important for me because of my work with Twitter bots and the lack of academic writing on social bots) . It was eye-opening for me to learn how some of these Twitter bots get developed and then sent into the wild to spam users. In the article, Exosaurs , (which is a bot created on Twitter) was given as an example of such bots. However, there are a lot more (e.g. @everyunicode) out there that were developed to spam users by integrating available datasets. Personally, the most interesting example shown in this article was the twitter bot that praises Fox new and includes the #PraiseFox: RealHumanPraise. The bot gained 31,000 followers in no time by real account.

It is important to realize that when bots like these might not be very harmful – other than spamming your twitter feed with a random tweet every 2 min – it could still harm or impact public opinion when used by governments in political unrest (e.g. Syrian Civil war) . Also, Bot creators are now becoming very good at developing extremely sophisticated Bots in a way that would make the tweets sound human-like.

I am excited that the Twitter bots are being brought to surface because I am sure with the rise of twitter bots we will encounter different ways in which these Bots will be employed in non traditional ways (e.g. marketing, politics ). As I mentioned earlier, this article is important to me and to other researchers working in this field because of the lake of reporting in this relatively new phenomenon. Currently, I am working on what we assume to be a Political Twitter BotNet with my team at the University of Washington.

I would like to hear from you, what did you think of the article?

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