UPM Institutional Repository

A study on detecting misleading online news using bigram and cosine similarity


Citation

Ishak, Iskandar and Che Eembi @ Jamil, Normala and Affendey, Lilly Suriani and Sidi, Fatimah (2018) A study on detecting misleading online news using bigram and cosine similarity. International Journal of Engineering and Technology (UAE), 7 (4.31). 242 - 245. ISSN 2227-524X

Abstract

Fake news can impact negatively in terms of creating negative perception towards business, organization, and government. One of the ways that fake news is created is through deceptive news writing. Many researchers have developed approaches in detecting deceptive news content using machine-learning approach and each of the approach has its own focus.Previous researches emphasis on the components of the news content such as in detecting grammar, humor, punctuation, body-dependent and body-independent features.In this paper, a new approach in detecting deceptive news based on misleading news has been developed which is focusing on the similarity between the content and its headlines using bigram and cosine similarity. Based on the experiments, the proposed approach has better performance in terms of detecting deceptive news.


Download File

[img] Text (Abstract)
FAKE.pdf
Download (5kB)

Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.14419/ijet.v7i4.31.23375
Publisher: Science Publishing Corporation
Keywords: Fake news; Deception; Lies; Misleading headlines; Deceiving news
Depositing User: Ms. Nuraida Ibrahim
Date Deposited: 27 Nov 2020 20:19
Last Modified: 27 Nov 2020 20:19
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.14419/ijet.v7i4.31.23375
URI: http://psasir.upm.edu.my/id/eprint/72998
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item