Here is an updated version of the paper "Big Data analytics and large-scale social events: the case of American Idol"
in which we consider the data from the final exhibitions aired yesterday night. Analyzing the data we made our real time predictions on the winner of the show. 
The result will be announced during the last show aired tonight at 8.00 PM EST.
(12.21 PM EST, May 23)

We have been working on pandemics and contagion phenomena long enough to deserve a little fun on a more frivolous but compelling case study for the debate about the predictive power of big data analytics.  In the new paper posted in the arxiv "Beating the news using social Media: the case study of American Idol" we focus on the elimination of contestants in the American Idol TV shows as an example of a well defined voting phenomenon that each week draws millions of votes in the USA.  We provide evidence that Twitter activity during the time span defined by the TV show airing and the voting period following it, correlates with the contestants ranking and allows the anticipation of the voting outcome. Furthermore, the fraction of Tweets that contain geolocation information allows us to map the fanbase of each contestant, both within the US and abroad, showing that strong regional polarizations occur. 
 We did not make any predictions about the final outcome of the show, yet. In order to infer the Top voted contestant we need the data that will become available on Tuesday May 22 night EST time and we will upload a revised manuscript before the the season finale.

After analyzing 120 million retweets connected to 12.5 million users and 1.3 million hashtags, we have recently published  in Scientific Reports the paper "Competition among memes in a world with limited attention". The paper, is a collaboration within the Truthy project, it's not so much the message intrinsic value but rather network structure and competition for attention that determine whether a meme becomes popular. The paper has been widely reported in the media. 

The Computational Approches to Social Modeling (ChASM) is a workshop organized by B. Gonçalves and N. Perra to bring together practitioners of both computer science and social science so that both may better understand the challenges faced by each other and how best they may collaborate to overcome them. 
The workshop is co-located with the International Conference on Computational Sciences (ICCS), Omaha, Nebraska, 4-6 June 2012. 
[Chasm: a profound difference between people, viewpoints, feelings, etc.]

Nature Physics has published an Insight issue about Complexity. The collection of articles surveys important progress in our fundamental understanding of what  seemingly disparate 'complex systems' have in common. Among the articles a review by Vespignani on Modelling dynamical processes in complex socio-technical systems. This article reviews the fundamental tools for modelling dynamical processes such as epidemic outbreaks and routing of information through computer networks  and discusses a number of applications.

Starting this fall the MoBS group has a new house and affiliation with Northeastern University in Boston, MA. The group is moving into a newly remodeled computational laboratory - the suite 132 - in the Nightingale Building on Forsyth Street. The laboratory has joint affiliations with the Department of Physics, the Department of Health Sciences and  the College of Computer and Information  Sciences. We thank the many friends and colleagues at Indiana University for the many years of exciting scientific work. We look forward to continuing collaborate with them in the future. At the same time we are excited to make new friends in the vibrant scientific community of Boston and to initiate new collaborations and research activities in our new academic home.