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Title: Towards tracking and analysing regional alcohol consumption patterns in the UK through the use of social media
Authors: Kershaw, Daniel
Rowe, Matthew
Stacey, Patrick K.
Keywords: Twitter
Keyword analysis
Trend detection
Issue Date: 2014
Publisher: Copyright is held by the owner/author(s). Publication rights licensed to ACM.
Citation: KERSHAW, D., ROWE, M. and STACEY, P., 2014. Towards tracking and analysing regional alcohol consumption patterns in the UK through the use of social media. IN: Proceedings of the 2014 ACM conference on Web science, Bloomington, IN, USA — June 23 - 26, 2014, pp. 220-228.
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 effect 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 sufficiently 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 introducing 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 consumption on National holidays and celebrations at both local and national levels.
Description: Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org.
Sponsor: This work is funded by the Digital Economy programme (RCUK Grant EP/G037582/1), which supports the High- Wire Centre for Doctoral Training (http://highwire.lancaster. ac.uk).
Version: Accepted for publication
DOI: 10.1145/2615569.2615678
URI: https://dspace.lboro.ac.uk/2134/22375
Publisher Link: http://dx.doi.org/10.1145/2615569.2615678
Appears in Collections:Conference Papers (Business School)

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