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A Platform for Exploring Social Media Analytics of Fast Food Restaurants in Australia

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Computational Science and Its Applications – ICCSA 2018 (ICCSA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10960))

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Abstract

Social media is one of the primary communication tools for Internet users. Twitter, one of the most popular social medias, has more than one hundred million daily active users. These tweeters tweet a large number of tweets every day containing a rich and diverse collection of information. At the same time, the problem of obesity is becoming a serious issue all over the world. In this paper, we consider the impact of the geographical location of fast food restaurant on the body mass index (BMI) and levels of obesity of individuals in Melbourne through data analytics around social media.

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References

  1. Hacker, J., Wickramasinghe, N., Durst, C.: Can health 2.0 address critical healthcare challenges? Insights from the case of how online social networks can assist in combatting the obesity epidemic. Australas. J. Inf. Syst. 21, 1–17 (2017)

    Google Scholar 

  2. Jensen, P., Jensen, L., Brunak, S.: Mining electronic health records: towards better research applications and clinical care. Nat. Rev. Genet. 13(6), 395–405 (2012)

    Article  Google Scholar 

  3. Sinnott, R.O., Cui, S.: Benchmarking sentiment analysis approaches on the cloud. In: 2016 IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS) (2016)

    Google Scholar 

  4. Hamed, A., Wu, X., Erickson, R., Fandy, T.: Twitter K-H networks in action: advancing biomedical literature for drug search. J. Biomed. Inf. 56, 157–168 (2015)

    Article  Google Scholar 

  5. Chae, B.: Insights from hashtag #supplychain and Twitter analytics: considering Twitter and Twitter data for supply chain practice and research. Int. J. Prod. Econ. 165, 247–259 (2015)

    Article  Google Scholar 

  6. Corso, A.J., Alsudais, K.: GIS, Big Data, and a tweet corpus operationalized via natural language processing. In: 21st Americas Conference on Information Systems (2015)

    Google Scholar 

  7. Kobayashi, S., Fujioka, T., Tanaka, Y., Inoue, M., Niho, Y., Miyoshi, A.: A geographical information system using the Google Map API for guidance to referral hospitals. J. Med. Syst. 34(6), 1157–1160 (2009)

    Article  Google Scholar 

  8. Putra, Y.A., Khodra, M.L.: A deep learning approach towards cross-lingual tweet tagging. In: 2016 International Conference on Data and Software Engineering (2016)

    Google Scholar 

  9. Lydecker, J.A., Cotter, E.W., Palmberg, A.A., Simpson, C., Kwitowski, M., White, K., Mazzeo, S.E.: Does this Tweet make me look fat? A content analysis of weight stigma on Twitter. Eat. Weight Disord. 21(2), 229–235 (2016)

    Article  Google Scholar 

  10. Anwar, M., Yuan, Z.: Linking obesity and tweets. In: Zheng, X., Zeng, D.D., Chen, H., Leischow, S.J. (eds.) ICSH 2015. LNCS, vol. 9545, pp. 254–266. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-29175-8_24

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. University of Melbourne, Melbourne, VIC, 3010, Australia

    Chang Liu & Richard O. Sinnott

Authors
  1. Chang Liu
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  2. Richard O. Sinnott
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Corresponding authors

Correspondence to Chang Liu or Richard O. Sinnott .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka shi, Fukuoka, Japan

    Bernady O. Apduhan

  9. Politecnico di Bari, Bari, Italy

    Eufemia Tarantino

  10. Myongji University, Yongin, Korea (Republic of)

    Yeonseung Ryu

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Liu, C., Sinnott, R.O. (2018). A Platform for Exploring Social Media Analytics of Fast Food Restaurants in Australia. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10960. Springer, Cham. https://doi.org/10.1007/978-3-319-95162-1_16

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  • DOI: https://doi.org/10.1007/978-3-319-95162-1_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95161-4

  • Online ISBN: 978-3-319-95162-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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