In 2019 it is estimated that there will be around 2.77 billion social media users around the globe.
In an era of mass social media use, where the general public can be considered as a sensor for reporting on emerging and on-going events, there is great potential to harness these communication channels.
However the complexities in realising these benefits are immense. Managing large data sets, using artificial intelligence to analyse and model social media interactions, and understanding and presenting real-time information as it occurs are just some of the challenges.
Professor Tom Jackson and Dr Ejovwoke Onojeharho from the Centre for Information Management (CIM), part of the University’s School of Business and Economics, have created a system that uses Twitter to detect and track a crisis situation.
TOXI-Motive can collect and analyse over 4,000 tweets a second, searching for key words, phrases and hashtags that could be linked to an emerging chemical, biological, nuclear or radiological (CBRN) incident.
It uses a detailed dashboard to present key data to incident commanders, providing on-the-ground information from the public as an emergency develops. It also acts as an important tool in combatting fake news, highlighting inaccurate information that may be being shared and enabling official sources to correct and target their communications.
The system is based on the team’s EMOTIVE program. First developed in 2012, EMOTIVE uses complex software to geographically map the emotional mood of the nation and its reaction to big events through Twitter. From high profile crimes to welfare reforms, the system can follow a specific event as it trends on Twitter and reveal how people are feeling about it. The program can also analyse how the public mood changes over time following subsequent incidents or interventions.