Predicting Online News Authorship by an Authorship Embeddings Space Method

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

doi:10.1109/ICBDA49040.2020.9101269

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 proceeding › Conference 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 language	English (US)
Title of host publication	2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	368-372
Number of pages	5
ISBN (Electronic)	9781728141114
DOIs	https://doi.org/10.1109/ICBDA49040.2020.9101269
State	Published - May 2020
Externally published	Yes
Event	5th IEEE International Conference on Big Data Analytics, ICBDA 2020 - Xiamen, China Duration: May 8 2020 → May 11 2020

Publication series

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

Conference

Conference	5th IEEE International Conference on Big Data Analytics, ICBDA 2020
Country	China
City	Xiamen
Period	5/8/20 → 5/11/20

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

Access to Document

10.1109/ICBDA49040.2020.9101269

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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

Predicting Online News Authorship by an Authorship Embeddings Space Method. / Wen, Wanting; Li, Qiudan; Li, Junfeng; Zhang, Xu; Zeng, Daniel.

2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 368-372 9101269 (2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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., 9101269, 2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020, Institute of Electrical and Electronics Engineers Inc., pp. 368-372, 5th IEEE International Conference on Big Data Analytics, ICBDA 2020, Xiamen, China, 5/8/20. https://doi.org/10.1109/ICBDA49040.2020.9101269

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

Wen, Wanting ; Li, Qiudan ; Li, Junfeng ; Zhang, Xu ; Zeng, Daniel. / Predicting Online News Authorship by an Authorship Embeddings Space Method. 2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 368-372 (2020 5th IEEE International Conference on Big Data Analytics, ICBDA 2020).

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