Advances in Personalized Healthcare Services, Wearable Mobile Monitoring, and Social Media Pervasive Technologies

Research Article

Tweet Analysis for User Health Monitoring

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  • @INPROCEEDINGS{10.4108/icst.mobihealth.2014.257537,
        author={Ranjitha Kashyap and Ani Nahapetian},
        title={Tweet Analysis for User Health Monitoring},
        proceedings={Advances in Personalized Healthcare Services, Wearable Mobile Monitoring, and Social Media Pervasive Technologies},
        publisher={IEEE},
        proceedings_a={APHS},
        year={2014},
        month={12},
        keywords={big data semantic analysis sentiment analysis twitter},
        doi={10.4108/icst.mobihealth.2014.257537}
    }
    
  • Ranjitha Kashyap
    Ani Nahapetian
    Year: 2014
    Tweet Analysis for User Health Monitoring
    APHS
    ICST
    DOI: 10.4108/icst.mobihealth.2014.257537
Ranjitha Kashyap1,*, Ani Nahapetian2
  • 1: Rubicon Project, Inc
  • 2: California State University Northridge, UCLA
*Contact email: ranjithabv@gmail.com

Abstract

Data analysis of social media postings can provide a wealth of information about the health of individual users, health across groups, and even access to healthy food choices in neighborhoods. In this paper, we analyze Twitter postings of 140 characters or less, known as tweets, to infer user health status over time. Tweets and in turn their users’ health are scored according to semantic analysis, sentiment analysis, emoticon classification, meta-data analysis, and profiling over time. The purpose of the analysis includes individually targeted healthcare personalization, determining health disparities, discovering health access limitations, advertising, and public health monitoring. The approach is analyzed on over 12,000 tweets spanning as far back as 2010 for 10 classes of users active on Twitter.