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XiaoA: A Robot Editor for Popularity Prediction of Online News Based on Ensemble Learning

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Intelligence Science II (ICIS 2018)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 539))

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Abstract

In this paper, we propose a robot editor called XiaoA to predict the popularity of online news. A method for predicting the popularity of online news based on ensemble learning is proposed with the component learners such as support vector machine, random forest, and neural network. The page view (PV) of news article is selected as the surrogate of popularity. A document embedding method Doc2vec is used as the basic analysis tool and the topic of the news is modeled by Latent Dirichlet Allocation (LDA). Experimental results demonstrate that our robot outperforms the state of the art method on popularity prediction.

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Authors and Affiliations

  1. Chinaso Inc., Beijing, 100077, China

    Fei Long, Meixia Xu, Yulei Li & Zhihua Wu

  2. Department of Automation, University of Science and Technology of China, Hefei, 230027, China

    Qiang Ling

Authors
  1. Fei Long
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  2. Meixia Xu
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  3. Yulei Li
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  4. Zhihua Wu
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  5. Qiang Ling
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Corresponding author

Correspondence to Fei Long .

Editor information

Editors and Affiliations

  1. Chinese Academy of Sciences, Beijing, China

    Zhongzhi Shi

  2. University of Amsterdam, Amsterdam, The Netherlands

    Cyriel Pennartz

  3. Peking University, Beijing, China

    Tiejun Huang

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Long, F., Xu, M., Li, Y., Wu, Z., Ling, Q. (2018). XiaoA: A Robot Editor for Popularity Prediction of Online News Based on Ensemble Learning. In: Shi, Z., Pennartz, C., Huang, T. (eds) Intelligence Science II. ICIS 2018. IFIP Advances in Information and Communication Technology, vol 539. Springer, Cham. https://doi.org/10.1007/978-3-030-01313-4_36

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  • DOI: https://doi.org/10.1007/978-3-030-01313-4_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01312-7

  • Online ISBN: 978-3-030-01313-4

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