A review of fake news detection approaches: A critical analysis of relevant studies and highlighting key challenges associated with the dataset, feature representation, and data fusion

Hamed, Suhaib Kh; Ab Aziz, Mohd Juzaiddin; Yaakub, Mohd Ridzwan

doi:10.1016/j.heliyon.2023.e20382

Cited by 20 publications

(4 citation statements)

References 68 publications

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“…These studies represent the state-of-the-art efforts in combating misinformation with AI. However, a key challenge in building an AI-based fake news classifier is related to datasets, feature representation, and data fusion [40].…”

Section: Fake News Detection Methodsmentioning

confidence: 99%

PL-NCC: A Novel Approach for Fake News Detection through Data Augmentation

Arunthavachelvan,

Hasan,

Ding

et al. 2024

Preprint

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Fake news has become rampant with the prominence of social media, jeopardizing information integrity and the reliability of news. It becomes imperative for media platforms to develop robust and efficient strategies to mitigate the spread of fake news. We make two contributions to fake news research in this work. Firstly, we propose the Psycho-Linguistic News Content and Comments (PL-NCC) dataset, a consolidated dataset of two leading fake news datasets, NELA-GT and Faked-dit, which leverages linguistic and psychological characteristics from the news articles and user comments to improve the classification accuracy of benchmark models. Secondly, we propose the News Content and Comments (NCC) classification model to leverage the psychological features extracted from our PL-NCC dataset, which introduces a feed-forward layer to a deep learning model, enhancing the efficacy of the extracted psychological features to better identify fake news. Our approach achieves a classification accuracy of over ninety percent, exceeding baseline results.

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Section: Fake News Detection Methodsmentioning

confidence: 99%

PL-NCC: A Novel Approach for Fake News Detection through Data Augmentation

Arunthavachelvan,

Hasan,

Ding

et al. 2024

Preprint

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“… Maharat-news fact-o-meter 11 : This is another factchecking website certified by IFCN. Their main focus is detecting rumors on online media in Lebanon and other Arab regions.…”

Section: Arabic Fact-checking Websitesmentioning

confidence: 99%

“…This paper working to focus in two aspects: features extraction techniques and the datasets used. This is because while classification algorithms play a critical role in fake news detection, their effectiveness heavily relies on the quality and relevance of the features provided to them [11]. Feature extraction techniques enable the models to capture the subtle nuances and contextual cues that differentiate fake news from real news [12].…”

Section: Introductionmentioning

confidence: 99%

A Review of Fake News Detection Techniques for Arabic Language

Alotaibi,

Al-Dossari

2024

IJACSA

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The growing proliferation of social networks provides users worldwide access to vast amounts of information. However, although social media users have benefitted significantly from the rise of various platforms in terms of interacting with others, e.g., expressing their opinions, finding products and services, and checking reviews, it has also raised critical problems, such as the spread of fake news. Spreading fake news not only affects individual citizens but also governments and countries. This situation necessitates the immediate integration of artificial intelligence methodologies to address and alleviate this issue effectively. Researchers in the field have leveraged different techniques to mitigate this problem. However, research in the Arabic language for fake news detection is still in its early stages compared with other languages, such as English. This review paper intends to provide a clear view of Arabic research in the field. In addition, the paper aims to provide other researchers working on solving Arabic fake news detection problems with a better understanding of the common features used in extraction, machine learning, and deep learning algorithms. Moreover, a list of publicly available datasets is provided to give an idea of their characteristics and facilitate researcher access. Furthermore, some of limitations and challenges related to Arabic fake news and rumor detection are discussed to encourage other researchers.

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“…Тому, надзвичайно важливим стало розрізняти, де саме є спотворення інформації. Існує кілька підходів до вирішення цього завдання: перевірка інформації вручну або автоматизована перевірка [6]. Розглядаючи метод ручної перевірки, можна виділити наступні переваги: людська інтуїція та досвід, складний аналіз контексту, гнучкість у розумінні нових моделей Однак, цей підхід має ряд недоліків: витратний час і обмежена продуктивність, суб'єктивність і неточність, нездатність обробляти великі обсяги даних, залежність від досвіду.…”

Section: постановка проблемиunclassified

Modern Approaches to Detecting and Combating Disinformation in Information Systems: Analysis and Improvement

Savitska,

Yurchak

2023

CDS

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This scientific article analyzes and characterizes various types of false information disseminated in modern information systems. The main focus is on detecting and identifying the dangers associated with the spread of unreliable information in society. The serious consequences of this phenomenon can reach a global scale, making effective countermeasures critically important. The study examines and compares various software methods to counter the dissemination of false information. In particular, different methods of analyzing and filtering information aimed at detecting and localizing unreliable messages were studied and compared. This helps identify the most effective approaches to data analysis in the field of information systems and determine optimal methods to combat the spread of fake news. The conclusions of this research have practical applications and can be used to improve the analysis of information from various sources in information systems. The implementation of the solutions developed in this research will contribute to increasing the level of credibility and objectivity in information processing, thereby enhancing the quality of information analysis and its utilization in various sectors of society.

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A review of fake news detection approaches: A critical analysis of relevant studies and highlighting key challenges associated with the dataset, feature representation, and data fusion

Cited by 20 publications

References 68 publications

PL-NCC: A Novel Approach for Fake News Detection through Data Augmentation

PL-NCC: A Novel Approach for Fake News Detection through Data Augmentation

A Review of Fake News Detection Techniques for Arabic Language

Modern Approaches to Detecting and Combating Disinformation in Information Systems: Analysis and Improvement

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