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A Scoping Review of the Relationship of Big Data Analytics with Context-Based Fake News Detection on Digital Media in Data Age

Sustainability, 2022-11, Vol.14 (21), p.14365 [Peer Reviewed Journal]

COPYRIGHT 2022 MDPI AG ;2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2071-1050 ;EISSN: 2071-1050 ;DOI: 10.3390/su142114365

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  • Title:
    A Scoping Review of the Relationship of Big Data Analytics with Context-Based Fake News Detection on Digital Media in Data Age
  • Author: Shahzad, Khurram ; Khan, Shakeel Ahmad ; Ahmad, Shakil ; Iqbal, Abid
  • Subjects: Age ; Algorithms ; Artificial intelligence ; Authenticity ; Big Data ; Computational linguistics ; Content analysis ; Context ; Data analysis ; Datasets ; Deep learning ; Digital broadcasting ; Digital media ; Digitization ; Disinformation ; Education ; False information ; Language processing ; Machine learning ; Natural language interfaces ; Neural networks ; Social media ; Social networks ; Sustainability ; Systematic review ; Unstructured data
  • Is Part Of: Sustainability, 2022-11, Vol.14 (21), p.14365
  • Description: The objectives of the study were to identify the relationship between big data analytics with context-based news detection on digital media in the data age, to find out the trending approaches to detect fake news on digital media, and to explore the challenges for constructing quality big data to detect misinformation on social media. Scoping review methodology was applied to carry out a content analysis of 42 peer-reviewed research papers published in 10 world-leading digital databases. Findings revealed a strong positive correlation between quality big data analytics and fake news detection on digital media. Additionally, it was found that artificial intelligence, fact-checking sites, neural networks, and new media literacy are trending techniques to identify correct information in the age of misinformation. Moreover, results manifested that hidden agenda, the volume of fake information on digital media, massive unstructured data, the fast spread of fake news on digital media, and fake user accounts are prevalent challenges to construct authentic big data for detecting false online information on digital media platforms. Theoretically, the study has added valuable literature to the existing body of knowledge by exploring the relationship between big data analytics and context-based fake news on digital media in the data age. This intellectual piece also contributes socially by offering practical recommendations to control the cancer of fake news in society for stopping horrific perils; hence, it has a societal impact. Current research has practical applications for generators of digital media applications, policy-makers, decision-takers, government representatives, civil societies, higher education bodies, media workforce, educationists, and all other stakeholders. Recommendations offered in the paper are a roadmap for framing impactful policies to stay away from the harms of fake digital news.
  • Publisher: Basel: MDPI AG
  • Language: English
  • Identifier: ISSN: 2071-1050
    EISSN: 2071-1050
    DOI: 10.3390/su142114365
  • Source: GFMER Free Medical Journals
    ROAD: Directory of Open Access Scholarly Resources
    ProQuest Central
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