What tweets can tell us about future
Can a flow of information across Twitter signal about a momentous future event? According to a new study, "yes" it can.
Washington DC: Can a flow of information across Twitter signal about a momentous future event? According to a new study, "yes" it can.
Northeastern's Alessandro Vespignani, Sternberg Family Distinguished University Professor of physics, computer science, and health sciences, has teamed up with an interdisciplinary group of scientists to develop an innovative method to map how tweets about large scale social events spread.
Using massive twitter datasets and sophisticated quantitative measures, it tracks how information about political protests, large business acquisitions, and other "collective phenomena" gather momentum, peak, and fall over time, from city to city, and where the impetus comes from for that trajectory.
The findings is only a first step, notes coauthor Nicola Perra. But knowing the characteristics of that buildup could, in the future, enable us to prepare ahead of time for undesirable repercussions from such events, with implications for crises from earthquakes to power grid failures.
"A lot of people have analyzed social media in terms of the volume of tweets regarding particular pheÂnomena such as the Arab Spring," says Vespignani. "What we are trying to understand is the presence of precursors: Can we find a signal in the flow of information that will tell us something big is about to happen? That's the multimillion dollar question."
In an interdisciplinary leap, the researchers turned to network modeling in neuroscience to conduct the study. "For the brain we map based on physiology, and for social aggreÂgates, like those in this paper, we map on geography," says Vespignani.
"Everyone wants to predict when the next big event is going to be, what will trend in the future," says Perra. "We are, as a research community, in the early stages of understanding this type of phenomena. There is very little understanding of even past events, so we are very far from prediction. But in the future our findings may lead us to that."
The study is published in the journal Science Advances.