Predicting Online News Authorship by an Authorship Embeddings Space Method

Wanting Wen, Qiudan Li, Junfeng Li, Xu Zhang, Daniel Zeng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we study the problem of authorship identification in online news data. Most of the existing approaches predict authorship via feature engineering, which cannot focus on important attributes. We designed an authorship identification method named Authorship Embeddings Space model (AES) to predict the online news authorship between online news and authors. First, we propose an authorship space to represent the deep semantic relationship of news content. Second, we use an embedding learning method to perform the relationship between authors and news. Finally, we formulated an authorship prediction algorithm to identify the news authors based on the authorship embeddings. Experimental results on the online news dataset reveal that the AES model outperforms the baseline models.

Original languageEnglish (US)
Title of host publication2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages368-372
Number of pages5
ISBN (Electronic)9781728141114
DOIs
StatePublished - May 2020
Externally publishedYes
Event5th IEEE International Conference on Big Data Analytics, ICBDA 2020 - Xiamen, China
Duration: May 8 2020May 11 2020

Publication series

Name2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020

Conference

Conference5th IEEE International Conference on Big Data Analytics, ICBDA 2020
CountryChina
CityXiamen
Period5/8/205/11/20

Keywords

  • Authorship identification
  • embeddings methods
  • online news authorship prediction

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management
  • Statistics, Probability and Uncertainty

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  • Cite this

    Wen, W., Li, Q., Li, J., Zhang, X., & Zeng, D. (2020). Predicting Online News Authorship by an Authorship Embeddings Space Method. In 2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020 (pp. 368-372). [9101269] (2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICBDA49040.2020.9101269