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Subjective Metrics-Based Cloud Market Performance Prediction

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Web Information Systems Engineering – WISE 2020 (WISE 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12342))

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Abstract

This paper explores an effective machine learning approach to predict cloud market performance for cloud consumers, providers and investors based on social media. We identified a set of comprehensive subjective metrics that may affect cloud market performance via literature survey. We used a popular sentiment analysis technique to process customer reviews collected from social media. Cloud market revenue growth was selected as an indicator of cloud market performance. We considered the revenue growth of Amazon Web Services as the stakeholder of our experiments. Three machine learning models were selected: linear regression, artificial neural network, and support vector machine. These models were compared with a time series prediction model. We found that the set of subjective metrics is able to improve the prediction performance for all the models. The support vector machine showed the best prediction results compared to the other models.

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Notes

  1. 1.

    https://www.g2crowd.com.

  2. 2.

    https://www.trustradius.com.

  3. 3.

    https://clutch.co/.

  4. 4.

    https://www.gartner.com/reviews/home.

  5. 5.

    https://www.whoishostingthis.com.

  6. 6.

    https://www.spiceworks.com.

  7. 7.

    https://www.qsrinternational.com/nvivo/home.

  8. 8.

    http://comp.social.gatech.edu/papers/.

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Author information

Authors and Affiliations

  1. School of Science, RMIT University, Melbourne, Australia

    Ahmed Alharbi & Hai Dong

Authors
  1. Ahmed Alharbi
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  2. Hai Dong
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Corresponding author

Correspondence to Hai Dong .

Editor information

Editors and Affiliations

  1. VU Amsterdam, Amsterdam, The Netherlands

    Zhisheng Huang

  2. VU Amsterdam, Amsterdam, The Netherlands

    Wouter Beek

  3. Victoria University, Melbourne, VIC, Australia

    Hua Wang

  4. Swinburne University of Technology, Hawthorn, VIC, Australia

    Rui Zhou

  5. Victoria University, Melbourne, VIC, Australia

    Yanchun Zhang

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Alharbi, A., Dong, H. (2020). Subjective Metrics-Based Cloud Market Performance Prediction. In: Huang, Z., Beek, W., Wang, H., Zhou, R., Zhang, Y. (eds) Web Information Systems Engineering – WISE 2020. WISE 2020. Lecture Notes in Computer Science(), vol 12342. Springer, Cham. https://doi.org/10.1007/978-3-030-62005-9_39

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  • DOI: https://doi.org/10.1007/978-3-030-62005-9_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62004-2

  • Online ISBN: 978-3-030-62005-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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