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SCIENCE CHINA Information Sciences, Volume 62, Issue 11: 219104(2019) https://doi.org/10.1007/s11432-018-9718-9

Inferring user profiles in social media by joint modeling of text and networks

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  • ReceivedMar 21, 2018
  • AcceptedDec 20, 2018
  • PublishedSep 18, 2019

Abstract

There is no abstract available for this article.


Acknowledgment

This work was supported by National Natural Science Foundation of China (Grant Nos. U1636103, 61632011, 61876053), Shenzhen Foundation Research Funding (Grant No. 20170307150024907), Key Technologies Research and Development Program of Shenzhen (Grant No. JSGG20170817140856618), and Innovate UK (Grant No. 103652).


References

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  • Table 1   Classification accuracy of our proposed model against baselines
    Baselines Gender Age Region
    LSTM 75.42 51.01 62.50
    LINE [5] 66.3051.8259.99
    SVM [6] 73.42 50.01 65.50
    CNN [7] 76.33 51.62 62.62
    Heterogeneous graph embedding [3] 81.33 74.39 60.92
    TOP in SMP [8] 88.30 64.80 72.70
    Our model 90.97 68.98 73.76
    Our model (Ensemble) 91.29 69.14 74.52

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