Half a million 2015 #marref tweets investigated by UL researchers



The UL based researchers, along with their international team, researched almost half a million tweets posted in connection with the 2015 marriage referendum

THE SENTIMENTS contained in tweets posted during a two-week run-up to the 2015 marriage referendum are the subject of investigation by two University of Limerick researchers.

David O’Sullivan and Professor James Gleeson at the Mathematics Applications Consortium for Science and Industry (MACSI) at UL joined Dr Guillermo Garduño-Hernández Sinnia, Mexico and Dr Mariano Beguerisse-Díaz University of Oxford, in investigating the sentiment contained in every tweet posted with the hashtags #marref and #marriageref.

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Their research showed that Twitter users were more likely to be connected with other users that shared their views in the marriage referendum.

Their results were documented in a paper published in the scientific journal “Royal Society Open Science”, after the team analysed nearly 500,000 tweets posted by over 100,000 unique Twitter users.

This resulted in an effective echo chamber for the spread of information, in the form of retweets.

Information was more likely to be trapped inside their group than shared outside. However, the analysis also showed that there was a committed core of active users on both sides of the referendum that actively engaged across ideological divisions.

Lead author MACSI PhD student David O’Sullivan explained why the research team chose to analyse tweets relating to this vote in particular.

“The marriage referendum posed a clear yes/no question in comparison to other, more complex votes such as Irish general elections where you have a ranked preference of outcomes.

“Also, the high volume of activity on Twitter relating to the Irish Marriage Referendum provided an excellent opportunity to understand how users interact around controversial or polarising topics. “

In the future, the research carried out can have potential applications in the integration of data and metadata to study opinion dynamics, public opinion modelling and polling, the team said.

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