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Stance and influence of Twitter users regarding the Brexit referendum

Overview of attention for article published in Computational Social Networks, July 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)

Mentioned by

1 blog
13 tweeters


52 Dimensions

Readers on

115 Mendeley
Stance and influence of Twitter users regarding the Brexit referendum
Published in
Computational Social Networks, July 2017
DOI 10.1186/s40649-017-0042-6
Pubmed ID

Miha Grčar, Darko Cherepnalkoski, Igor Mozetič, Petra Kralj Novak


Social media are an important source of information about the political issues, reflecting, as well as influencing, public mood. We present an analysis of Twitter data, collected over 6 weeks before the Brexit referendum, held in the UK in June 2016. We address two questions: what is the relation between the Twitter mood and the referendum outcome, and who were the most influential Twitter users in the pro- and contra-Brexit camps? First, we construct a stance classification model by machine learning methods, and are then able to predict the stance of about one million UK-based Twitter users. The demography of Twitter users is, however, very different from the demography of the voters. By applying a simple age-adjusted mapping to the overall Twitter stance, the results show the prevalence of the pro-Brexit voters, something unexpected by most of the opinion polls. Second, we apply the Hirsch index to estimate the influence, and rank the Twitter users from both camps. We find that the most productive Twitter users are not the most influential, that the pro-Brexit camp was four times more influential, and had considerably larger impact on the campaign than the opponents. Third, we find that the top pro-Brexit communities are considerably more polarized than the contra-Brexit camp. These results show that social media provide a rich resource of data to be exploited, but accumulated knowledge and lessons learned from the opinion polls have to be adapted to the new data sources.

Twitter Demographics

The data shown below were collected from the profiles of 13 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 115 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 23%
Student > Ph. D. Student 21 18%
Student > Bachelor 13 11%
Researcher 7 6%
Student > Postgraduate 5 4%
Other 16 14%
Unknown 27 23%
Readers by discipline Count As %
Computer Science 31 27%
Social Sciences 25 22%
Business, Management and Accounting 5 4%
Arts and Humanities 5 4%
Economics, Econometrics and Finance 4 3%
Other 15 13%
Unknown 30 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 April 2022.
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Altmetric has tracked 21,078,563 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 40 research outputs from this source. They receive a mean Attention Score of 3.7. This one scored the same or higher as 38 of them.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 287,583 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them