Featured Research

from universities, journals, and other organizations

System detects global trends in social networks two months in advance

Date:
April 28, 2014
Source:
Universidad Carlos III de Madrid - Oficina de Información Científica
Summary:
A new method of monitoring identifies what information will be relevant on social networks up to two months in advance. This may help predict social movements, consumer reactions or possible outbreaks of epidemics, according to a study. The system works using just 50,000 Twitter accounts, predicting what will "go viral" across the entire Internet. It can be used in real time, about different topics, in different languages and geographical areas, thus allowing for different contexts to be covered.

Left, cascade of the “viral” spread of hashtag #openwebawards. Right, how sensors are chosen: using a set of randomly selected users (C) some followers are framed in the sensor-friends group (S). These occupy a more central position in the web and, therefore, find out about information and spread it before others.
Credit: Image courtesy of Universidad Carlos III de Madrid - Oficina de Información Científica

A new method of monitoring identifies what information will be relevant on social networks up to two months in advance. This may help predict social movements, consumer reactions or possible outbreaks of epidemics, according to a study in the Universidad Carlos III of Madrid (UC3M) is participating.

Related Articles


The aim of the research, on which scientists from the Universidad Autónoma of Madrid, the NICTA of Australia, and the American universities Yale and the University of California-San Diego have also collaborated, was to test what is known as the "sensors hypothesis" on the social networks: Is it possible to find a group of people (sentinels or sensors) with a special position that would allow the information that "goes viral" globally on the internet to be monitored? "If we could do that, we would be able to predict that viral spread, which would allow us to better understand social mobilization, debates regarding opinions, health, etc., and to determine how they become global," explains one of the researchers, Esteban Moro Egido, of the Interdisciplinary Complex Systems Group at UC3M (Grupo Interdisciplinar de Sistemas Complejos).

To do this, the scientists made use of one of the properties of the social networks that can also be observed in Twitter; it is known as "the friendship paradox": your friends have, on average, more friends than you. In the case of Twitter, after analyzing a sample of data from 40 million users and 15 billion followers in 2009, the researchers were able to show that each user had an average of 25 followers, who in turn had an average of 422 followers, that is, almost twenty times as many. "This means that a person's followers have a role in a social network that makes them very relevant when it comes to spreading or receiving information," explains another of the researchers, Manuel García Herranz, of the Computer Engineering Department at the Universidad Autónoma of Madrid.

What they have done in this study, which has been published in the journal PLoS ONE, is to randomly select a group of users and take some of their followers as the sensor group. And what they have found out is that those "sensor-friends" play a more important role than what was previously believed, because they receive information long before the previously chosen users. "We were really surprised. We thought the method would give us a few hours early warning, but instead it gave us several days, and sometimes even weeks or months," says co-senior author of the authors, James Fowler, professor of medical genetics and political science at the University of California-San Diego (USA). For example, the sensor model predicted the "viral" rise of the hashtag "#Obamacare" as a Twitter trend, detecting it two months before it peaked on Twitter, and three months before it reached the highest number of Google searches with that name.

Simple and effective

In general, this new method turns out to be very simple and effective for monitoring social networks, according to its creators. Data from just 50,000 Twitter is enough to achieve these levels of prediction and to know what will "go viral" across the entire Internet. It can be used in real time, about different topics, in different languages and geographical areas, thus allowing for different contexts to be covered: discovering new opinions in a political debate, predicting social movements, obtaining previous knowledge of consumers' reactions to new products, or analyzing how messages regarding certain illnesses or epidemics are spread in the public health arena.

This system has certain limitations. It cannot predict how information associated with a particular event, such as a football match, or daily news or natural disasters is going to spread "virally," the scientists warn. However, there are other types of news that it is able to predict, such as social movements (the 15M in Madrid) or ideas that have been moving around the web for a while on a small scale and then later reach the general public. "We found that monitoring social media in this manner offers a whole new way of monitoring the global spread of information about all sorts of topics," comments another one of the researchers, Nicholas Christakis, co-director of the Yale Institute for Network Science, USA. This is undoubtedly a new way of predicting the future by analyzing the data that circulates on the social networks.

Video Youtube:

https://www.youtube.com/watch?v=KlfmZNzZXVg


Story Source:

The above story is based on materials provided by Universidad Carlos III de Madrid - Oficina de Información Científica. Note: Materials may be edited for content and length.


Journal Reference:

  1. Manuel Garcia-Herranz, Esteban Moro, Manuel Cebrian, Nicholas A. Christakis, James H. Fowler. Using Friends as Sensors to Detect Global-Scale Contagious Outbreaks. PLoS ONE, 2014; 9 (4): e92413 DOI: 10.1371/journal.pone.0092413

Cite This Page:

Universidad Carlos III de Madrid - Oficina de Información Científica. "System detects global trends in social networks two months in advance." ScienceDaily. ScienceDaily, 28 April 2014. <www.sciencedaily.com/releases/2014/04/140428094211.htm>.
Universidad Carlos III de Madrid - Oficina de Información Científica. (2014, April 28). System detects global trends in social networks two months in advance. ScienceDaily. Retrieved October 31, 2014 from www.sciencedaily.com/releases/2014/04/140428094211.htm
Universidad Carlos III de Madrid - Oficina de Información Científica. "System detects global trends in social networks two months in advance." ScienceDaily. www.sciencedaily.com/releases/2014/04/140428094211.htm (accessed October 31, 2014).

Share This



More Computers & Math News

Friday, October 31, 2014

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

Samsung's Incredible Shrinking Smartphone Profits

Samsung's Incredible Shrinking Smartphone Profits

Reuters - Business Video Online (Oct. 30, 2014) — The world's top mobile maker is under severe pressure, delivering a 60 percent drop in Q3 profit as its handset business struggles. Turning it around may not prove easy, says Reuters' Jon Gordon. Video provided by Reuters
Powered by NewsLook.com
Ban On Wearable Cameras In Movie Theaters Surprises No One

Ban On Wearable Cameras In Movie Theaters Surprises No One

Newsy (Oct. 30, 2014) — The Motion Picture Association of America and the National Association of Theatre Owners now prohibit wearable cameras such as Google Glass. Video provided by Newsy
Powered by NewsLook.com
Spain's New 'Google Tax' Makes News Feeds Pay For Links

Spain's New 'Google Tax' Makes News Feeds Pay For Links

Newsy (Oct. 30, 2014) — Spanish lawmakers have passed new IP rules requiring aggregators to pay for linking to news sites, following a broader trend across the E.U. Video provided by Newsy
Powered by NewsLook.com
Microsoft Launches Fitness Band After Accidental Reveal

Microsoft Launches Fitness Band After Accidental Reveal

Newsy (Oct. 30, 2014) — Microsoft accidentally revealed its upcoming fitness band on Wednesday, so the company went ahead and announced it. Video provided by Newsy
Powered by NewsLook.com

Search ScienceDaily

Number of stories in archives: 140,361

Find with keyword(s):
 
Enter a keyword or phrase to search ScienceDaily for related topics and research stories.

Save/Print:
Share:  

Breaking News:

Strange & Offbeat Stories

 

Space & Time

Matter & Energy

Computers & Math

In Other News

... from NewsDaily.com

Science News

Health News

Environment News

Technology News



Save/Print:
Share:  

Free Subscriptions


Get the latest science news with ScienceDaily's free email newsletters, updated daily and weekly. Or view hourly updated newsfeeds in your RSS reader:

Get Social & Mobile


Keep up to date with the latest news from ScienceDaily via social networks and mobile apps:

Have Feedback?


Tell us what you think of ScienceDaily -- we welcome both positive and negative comments. Have any problems using the site? Questions?
Mobile iPhone Android Web
Follow Facebook Twitter Google+
Subscribe RSS Feeds Email Newsletters
Latest Headlines Health & Medicine Mind & Brain Space & Time Matter & Energy Computers & Math Plants & Animals Earth & Climate Fossils & Ruins