Political surveys have indicated a relationship between a sense of Scottish identity and voting decisions in the 2014 Scottish Independence Referendum. Identity is often reflected in language use, suggesting the intuitive hypothesis that individuals who support Scottish independence are more likely to use distinctively Scottish words than those who oppose it. In the first large-scale study of sociolinguistic variation on social media in the UK, we identify distinctively Scottish terms in a data-driven way, and find that these terms are indeed used at a higher rate by users of pro-independence hashtags than by users of anti-independence hashtags. However, we also find that in general people are less likely to use distinctively Scottish words in tweets with referendum-related hashtags than in their general Twitter activity. We attribute this difference to style-shifting relative to audience, aligning with previous work showing that Twitter users tend to use fewer local variants when addressing a broader audience.
|Title of host publication||European Chapter of the Association for Computational Linguistics (EACL 2017)|
|Place of Publication||Valencia, Spain|
|Publisher||Association for Computational Linguistics|
|Number of pages||10|
|Publication status||Published - 7 Apr 2017|
|Event||15th EACL 2017 Software Demonstrations - Valencia, Spain|
Duration: 3 Apr 2017 → 7 Apr 2017
|Conference||15th EACL 2017 Software Demonstrations|
|Abbreviated title||EACL 2017|
|Period||3/04/17 → 7/04/17|
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- School of Informatics - Personal Chair of Computational Language Learning
- Institute of Language, Cognition and Computation
- Language, Interaction and Robotics
Person: Academic: Research Active