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Research on multi-label user classification of social media based on ML-KNN algorithm

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  • Huang, Anzhong
  • Xu, Rui
  • Chen, Yu
  • Guo, Meiwen

Abstract

Several research studies have been conducted on multi-label classification algorithms for text and images, but few have been conducted on multi-label classification for users. Moreover, the existing multi-label user classification algorithm does not provide an effective representation of users, and it is difficult to use directly in social media scenarios. By analyzing complex social networks, this paper aims to achieve multi-label classification of users based on research in single-label classification.

Suggested Citation

  • Huang, Anzhong & Xu, Rui & Chen, Yu & Guo, Meiwen, 2023. "Research on multi-label user classification of social media based on ML-KNN algorithm," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    • Handle: RePEc:eee:tefoso:v:188:y:2023:i:c:s0040162522007922
    DOI: 10.1016/j.techfore.2022.122271
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    References listed on IDEAS

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    3. Saleha Noor & Yi Guo & Syed Hamad Hassan Shah & M. Saqib Nawaz & Atif Saleem Butt, 2020. "Research Synthesis and Thematic Analysis of Twitter Through Bibliometric Analysis," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 16(3), pages 88-109, July.
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    1. Xing, Yunfei & Zhang, Justin Zuopeng & Teng, Guangqing & Zhou, Xiaotang, 2024. "Voices in the digital storm: Unraveling online polarization with ChatGPT," Technology in Society, Elsevier, vol. 77(C).

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