New! Sign up for our free email newsletter.
Science News
from research organizations

What social media data could tell us about the future

New research tracks tra­jec­tory of tweets to spot pre­cur­sors of large social events

April 7, 2016
Northeastern University
Can a flow of information across Twitter signal when a momentous event is about to occur? Scientists developed a method to find out. Their findings represent an initial step in constructing models to detect trouble before it's too late.

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, pub­lished Friday in the journal Science Advances, is only a first step, notes coau­thor Nicola Perra, a former research asso­ciate at Northeastern's Net­work Sci­ence Insti­tute. 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 phe­nomena such as the Arab Spring," says Vespig­nani, who is also the director of the Net­work Sci­ence Insti­tute. "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 aggre­gates, like those in this paper, we map on geog­raphy," says Vespignani.

In neu­ro­science net­work mod­eling, the "nodes," or cen­ters of activity, are func­tional brain areas--say, the motor cortex, which is respon­sible for movement--and the "links" con­necting the nodes are neural cir­cuits. For example, the cir­cuits con­necting the motor cortex to the audi­tory cortex, which is respon­sible for hearing, trace a neural pathway, or "link," that enables us to tap our foot to a beat and even dance.

In this new, social- events study, the nodes are cities--for example, Madrid and Barcelona in the researchers' analysis of twitter trans­mis­sion during the 2011 Spanish anti- austerity movement--and the links are the path­ways the tweets take over time.

Con­sider the Spanish protest, which later sparked the Occupy Wall St. move­ment in the U.S. The tweets gained in volume and inten­sity until, says Vespig­nani, they reached a "social tip­ping point of col­lec­tive phe­nom­enon" on May 20, 2011. "You create a system that starts from a few nodes that then drive others, and so on, until every­body is talking to every­body else in a full coor­di­na­tion of the infor­ma­tion," he explains.

The quan­ti­ta­tive iden­ti­fi­ca­tion of those dri­vers sets this new method apart from other approaches to tracking social media, says Perra, who is now a senior lec­turer at London's Uni­ver­sity of Green­wich. "It enables us to under­stand which city is dri­ving the con­ver­sa­tion when and to char­ac­terize the dynamics of the spread."

"Before you can develop a method to pre­dict future events," he adds, "you need a quan­ti­ta­tive under­standing of the com­mu­nica­tion pat­terns that shaped past events."

Laying the ground­work for pre­dic­tive studies is what Vespig­nani and his col­leagues are attempting to do with this analysis of five major social events: the 2011 protest in Spain; the 2013 protest in Brazil, known as the "Brazilian Autumn"; the release of a Hol­ly­wood block­buster in 2012; and Google's acqui­si­tion of Motorola in 2014.

"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."

Story Source:

Materials provided by Northeastern University. Note: Content may be edited for style and length.

Journal Reference:

  1. J. Borge-Holthoefer, N. Perra, B. Goncalves, S. Gonzalez-Bailon, A. Arenas, Y. Moreno, A. Vespignani. The dynamics of information-driven coordination phenomena: A transfer entropy analysis. Science Advances, 2016; 2 (4): e1501158 DOI: 10.1126/sciadv.1501158

Cite This Page:

Northeastern University. "What social media data could tell us about the future." ScienceDaily. ScienceDaily, 7 April 2016. <>.
Northeastern University. (2016, April 7). What social media data could tell us about the future. ScienceDaily. Retrieved March 1, 2024 from
Northeastern University. "What social media data could tell us about the future." ScienceDaily. (accessed March 1, 2024).

Explore More
from ScienceDaily