Towards tracking and analysing regional alcohol consumption patterns in the UK through the use of social media

Stacey, Patrick and Kershaw, Daniel and Rowe, Matthew (2014) Towards tracking and analysing regional alcohol consumption patterns in the UK through the use of social media. In: Web Science Conference 2014, 2014-06-232014-06-26, Indiana.

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Abstract

Monitoring rates of alcohol consumption across the UK is a timely problem due to ever-increasing drinking levels [36]. This has led to calls from public services (e.g. police and health services) to assess the e↵ect it is having on people and society. Current research methods that are utilised to assess consumption patterns are costly, time consuming, and do not supply su␣ciently detailed results. This is because they look at snapshots of individuals’ drinking patterns, which rely on generalised usage patterns, and post consumption re- call. In this paper we look into the use of social media such as Twitter (a popular micro blogging site) to monitor the rate of alcohol consumption in regions across the UK by introduc- ing the Social Media Alcohol Index (SMAI). By looking at the variation in term usage, and treating the social network as a spatio-temporal self-reporting sense-network, we aim to discover variation in drinking patterns on both local and national levels within the UK. This study used 31.6 million tweets collected over a 6 week period, and used the Health & Social Care Information Centre (HSCIC) weekly alcohol consumption pattern as a ground truth. High correlations between the ground truth and the computed SMAI (Social Media Alcohol Index) were found on a national and local level, along with the ability to detect variation in consump- tion on National holidays and celebrations at both local and national levels.

Item Type:
Contribution to Conference (Paper)
Journal or Publication Title:
Web Science Conference 2014
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/aacsb/disciplinebasedresearch
Subjects:
?? TWITTERSNSKEYWORD ANALYSISALCOHOLTREND DETECTIONBIG DATADISCIPLINE-BASED RESEARCH ??
ID Code:
69403
Deposited By:
Deposited On:
07 May 2014 10:55
Refereed?:
Yes
Published?:
Published
Last Modified:
21 Sep 2023 04:14