Clickbait detection: A literature review of the methods used

Authors

  • Nurrida Aini Zuhroh Institut Teknologi Sepuluh Nopember, Surabaya
  • Nur Aini Rakhmawati Institut Teknologi Sepuluh Nopember, Surabaya

DOI:

https://doi.org/10.26594/register.v6i1.1561

Keywords:

clikbait, deep learning, literature review, machine learning, word embedding

Abstract

Online news portals are currently one of the fastest sources of information used by people. Its impact is due to the credibility of the news produced by actors from the media industry, which is sometimes questioned. However, one of the problems associated with this medium used to obtain information is clickbait. This technique aims to attract users to click hyperbolic headlines with content that often disappoints the reader. This study was, therefore, conducted to determine: 1) existing dataset available. 2) The method used in clickbait detection which consists of data preprocessing, analysis of features, and classification. 3) Difference steps from the method used.

Author Biographies

Nurrida Aini Zuhroh, Institut Teknologi Sepuluh Nopember, Surabaya

Information Systems Department

Nur Aini Rakhmawati, Institut Teknologi Sepuluh Nopember, Surabaya

Information Systems Department

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Published

2020-01-01

How to Cite

[1]
N. A. Zuhroh and N. A. Rakhmawati, “Clickbait detection: A literature review of the methods used”, Register: Jurnal Ilmiah Teknologi Sistem Informasi, vol. 6, no. 1, pp. 1–10, Jan. 2020.

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