Mathematics student develops model that can predict trends via Twitter

Sep 24, 2013

University of Twente student Marijn ten Thij has developed a mathematical model that can simulate the emergence of trends via Twitter. This model makes it simpler to understand how trends emerge on Twitter and how they develop further. According to ten Thij, "With this model, we can predict if a topic on Twitter will develop into a trend or an event in real life".

Ten Thij used three data sets with tweets to develop the mathematical model, one of which consisted of on Project X in Haren. Ten Thij analyzed all of the retweets about the event in the period before and right after the riots. The mathematics student purposefully omitted any information about the Twitter users themselves from consideration in his research. For example, his research did not include whether a particular Twitter user was influential, such as a Dutch celebrity. He wanted to see, independent of the , if he could predict a trend. Ten Thij: "You often see different groups of people talking with one another about the same topic on Twitter, for example, in Twente, in Amsterdam and a group in Eindhoven. The point at which a trend may emerge on Twitter is the moment at which these groups also connect with each other".

Trend detection

Ten Thij entered the retweets on Project X into a smart that can simulate how Twitter users are connected to each other through retweets. "If a trend is connected with an event in real life, we see that different user groups retweet each other's messages and that users more frequently tweet on the same topic. In the Project X data, we see this a day before the event itself happens."

Nelly Litvak, senior lecturer in the department of Stochastic Operational Research and ten Thij's supervisor: "I was awarded a grant by Google for our research into detection and we will certainly continue with our work. The future can never be predicted with 100% certainty, but we strive to provide answers with a high degree of certainty."

Marijn ten Thij studied Applied Mathematics at the University of Twente. He recently graduated from the department of Stochastic Operations Research under Prof. Richard J. Boucherie, PhD. This research is carried out at the Centre for Telematics and Information Technology (CTIT). Dr Nelly Litvak was Ten Thij's supervisor. He completed his thesis, titled "Modelling trends in social media", at TNO (Netherlands Organisation for Applied Scientific Research) within the Performance of Networks and Systems expertise group (PONS).

Explore further: Computerized emotion detector

add to favorites email to friend print save as pdf

Related Stories

Twitter opens window into user activities

Nov 15, 2011

Twitter on Monday finished adding features that let users see who likes their posts and what the people they follow are doing at the popular microblogging network.

Twitter says its ads pay off for candidates

Oct 10, 2012

Twitter released a study Wednesday showing its paid messages pay off for political candidates, not only in garnering attention but in driving campaign contributions.

Recommended for you

Computerized emotion detector

Sep 16, 2014

Face recognition software measures various parameters in a mug shot, such as the distance between the person's eyes, the height from lip to top of their nose and various other metrics and then compares it with photos of people ...

Cutting the cloud computing carbon cost

Sep 12, 2014

Cloud computing involves displacing data storage and processing from the user's computer on to remote servers. It can provide users with more storage space and computing power that they can then access from anywhere in the ...

Teaching computers the nuances of human conversation

Sep 12, 2014

Computer scientists have successfully developed programs to recognize spoken language, as in automated phone systems that respond to voice prompts and voice-activated assistants like Apple's Siri.

Mapping the connections between diverse sets of data

Sep 12, 2014

What is a map? Most often, it's a visual tool used to demonstrate the relationship between multiple places in geographic space. They're useful because you can look at one and very quickly pick up on the general ...

User comments : 2

Adjust slider to filter visible comments by rank

Display comments: newest first

Stephen_Crowley
not rated yet Sep 24, 2013
Now if there was anything of any value on twitter or anyone who used it to make more than a sarcastic idiotic response
antialias_physorg
5 / 5 (1) Sep 24, 2013
I can already see the downside of this (not knocking the research. It's certainly very interesting). But such analysis would give oppressive regimes/secret services a means to predict which nodes (people) need to be taken out of the loop to prevent a potential rebellion from spreading or some unwanted news from going viral..