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

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    17 Scopus citations

    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 suffciently 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.

    Original languageEnglish
    Title of host publicationWebSci 2014 - Proceedings of the 2014 ACM Web Science Conference
    PublisherAssociation for Computing Machinery
    Pages220-228
    Number of pages9
    ISBN (Print)9781450326223
    DOIs
    StatePublished - Jun 23 2014
    Event6th ACM Web Science Conference, WebSci 2014 - Bloomington, IN, United States
    Duration: Jun 23 2014Jun 26 2014

    Publication series

    NameWebSci 2014 - Proceedings of the 2014 ACM Web Science Conference

    Conference

    Conference6th ACM Web Science Conference, WebSci 2014
    Country/TerritoryUnited States
    CityBloomington, IN
    Period06/23/1406/26/14

    Keywords

    • Alcohol
    • Keyword analysis
    • SNS
    • Trend detection
    • Twitter

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