The discovery of the Higgs boson was one of the landmark discoveries of 2012 and it will be remembered forever in the history of science. The news was shared around the World within minutes of the CERN announcement. Dr Mirco Musolesi’s paper ‘The Anatomy of Scientific Rumor’ published in Nature Scientific Reports and awarded Best Paper October 2013, presents a study of the spread of communication on Twitter around the time of the announcement and explores the increasingly important role social media takes in the communication of science and in the scholarly debate. 

By Dr Mirco Musolesi

The discovery of the Higgs boson was one of the landmark discoveries of the year 2012 and it will be remembered forever in the history of science. The existence of the Higgs boson was hypothesized in 1964 by a group of scientists including and François Englert in 1964. Higgs and Englert won the 2013 Nobel prize in Physics for this work. After the publication of that series of papers in the Sixties, the search for the existence of the Higgs-boson has been among the top research priorities of the particle physics community for the past decades. The search was over on 4th July 2012 when the ATLAS and CMS collaborations, two international experiments involved in the hunt for the Higgs boson, announced the discovery of a new particle with the features of the particle theoretically predicted by Higgs and other physicists 50 years before.  This was the missing component of the Standard Model, a comprehensive theory concerning the electromagnetic, weak, and strong nuclear interactions that are involved in the dynamics of subatomic particles.  

The elusive nature of the Higgs boson required the development of a new generation of large-scale experimental facilities, resulting in the construction of the Large Hadron Collider (LHC) at CERN, in Genéve, Switzerland, the largest and most powerful particle accelerator ever built. There was also a sort of "rival" consortium based at the Tevatron in Batavia, Illinois. The association of the Higgs boson to the idea of the final understanding of our Universe and the possibility of the Grand Unified Theory is likely to be responsible for the incredible popularity of this research project in both academic and non-academic circles. Indeed, the interest from both specialized and popular media increased after the name “God particle” was assigned to the Higgs boson in a book published in 1993 (it is worth noting that Higgs did not like this sort of sensationalism).

Indeed, there was also an amazing interest on social media, in particular on Twitter, which is playing an increasingly important role in the communication of science and in the scholarly debate in general. And this was also an exceptional occasion for us to analyse the dynamics of information spreading of a global event in Twitter.

In our Nature Scientific Reports paper we present a study of information spreading processes on Twitter before, during and after the announcement of the discovery of a new particle with the features of the elusive Higgs boson on 4th July 2012. In other words, we study how the initial rumours about the discovery spread on Twitter in the days before the official announcement and what happened after that.

The paper contains a model of the spreading of the "scientific rumour" in the network of individuals that are present in Twitter. Twitter can be seen as a network where the users are the nodes and the links (edges) correspond to the followers/followees relationships. Our model was evaluated by means of the complete dataset of tweets containing the hashtags: lhc, cern, boson and higgs. We downloaded this dataset using an open programming interface that is made available by Twitter. The dataset included tweets made by 500,000 individuals, including tweets, re-tweets and replies to existing tweets. In the paper we show that our model is able to reproduce the global spreading of the information with remarkable accuracy. The information dissemination model is inspired by the spreading of epidemics. Like diseases, information spreads in the social network of individuals reaching all the continents.

We followed the complete series of events from 1st to 7th July. Let us recap the key events on those days. On 2nd July, initial results were presented by the Tevatron team in the United States, but they were not sufficient to claim a scientific discovery. In order to claim a discovery, you need to show that there is a high degree of certainty that you are not observing a random event or a glitch in your data. Although these results were of great interest for the scientific community, such an announcement had a weak impact on the general public. Following this, there was a strong expectation, accompanied by rumours, for the corresponding results from the CERN teams. Quite interestingly, an unofficial video was even leaked during those days. The spreading of these rumours about a possible discovery attracted the interest of media, also outside the academic community, until the official day of the announcement on 4th July during the International Conference on High-Energy Physics in Melbourne. Yes, the elusive particle was not elusive anymore. In our dataset we observe "spikes" of interest and change of "behaviour" in Twitter corresponding to these key events.

So why is this research work interesting?

First of all, it is worth noting that for the first time in history we are able to study global phenomena from a quantitative point of view. This was not possible just a few years ago. Then, the possibility of modelling the spreading of information on Twitter opens very interesting prospects also from an application point of view. If you know how a piece of information spreads on a network, you might be able to control its diffusion. Possible applications include marketing (how can you maximise the diffusion of a certain advertisement?) or emergency response (how can authorities spread important information to the population in an efficient way? How can you stop the spreading of false information)? 

But we are just at the beginning. The era of big (social) data has just started in a sense.

Manlio De Domenico, Antonio Lima, Paul Mougel and Mirco Musolesi

Nature Scientific Reports. 3:2980. Nature Publishing Group. October 2013