A Systematic Literature Review and Meta-Analysis of Studies on Online Fake News Detection

Abstract

The ubiquitous access and exponential growth of information available on social media networks have facilitated the spread of fake news, complicating the task of distinguishing between this and real news. Fake news is a significant social barrier that has a profoundly negative impact on society. Despite the large number of studies on fake news detection, they have not yet been combined to offer coherent insight on trends and advancements in this domain. Hence, the primary objective of this study was to fill this knowledge gap. The method for selecting the pertinent articles for extraction was created using the preferred reporting items for systematic reviews and meta-analyses (PRISMA). This study reviewed deep learning, machine learning, and ensemble-based fake news detection methods by a meta-analysis of 125 studies to aggregate their results quantitatively. The meta-analysis primarily focused on statistics and the quantitative analysis of data from numerous separate primary investigations to identify overall trends. The results of the meta-analysis were reported by the spatial distribution, the approaches adopted, the sample size, and the performance of methods in terms of accuracy. According to the statistics of between-study variance high heterogeneity was found with τ2 = 3.441; the ratio of true heterogeneity to total observed variation was I2 = 75.27% with the heterogeneity chi-square (Q) = 501.34, the degree of freedom = 124, and p ≤ 0.001. A p-value of 0.912 from the Egger statistical test confirmed the absence of a publication bias. The findings of the meta-analysis demonstrated satisfaction with the effectiveness of the recommended approaches from the primary studies on fake news detection that were included. Furthermore, the findings can inform researchers about various approaches they can use to detect online fake news.

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“…One of the finest techniques for helping researchers do systematic reviews and meta-analyses correctly and review a structure like a road map is PRISMA. This approach is well-liked in systematics literature and has been widely applied in a variety of research [24][25][26][27][28]80]. The scientific literature that can be obtained using a structured approach that is based on objectives that are set so that different authors can utilize them can be summarized and analyzed by the researcher in a systematic review, which provides significant evidence [29].…”

Conceptual change management framework for effective use of examination administration system: a systemic review

“…Following the first literature search in the databases, using criteria espoused in this paper, for example, the reports were filtered by applicability (Thompson et al, 2022;Vargo et al, 2020) and the selected reports were reduced to 153. There 153 reports were further filtered looking for the English written, and publication dated of between 2015 and 2023.…”

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

“…This emphasizes the significance of testing fake news detection models using several samples. Moreover, a significant factor in variability was the sample size used to define the detection accuracy [ 83 ]. Several datasets are available in the field of fake news detection; however, there are some restrictions, such as size, modality, and granularity, in addition to being outdated [ 69 ].…”