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Cite this DOI

10.46243/jst.2023.v8.i07.pp184-192 · IDENTIFYING AND PREVENTING THE DISSEMINATION OF FAKE NEWS

APA (7th edition)

Syed Salman Hussain, S. S. H. (2023). IDENTIFYING AND PREVENTING THE DISSEMINATION OF FAKE NEWS. *Journal of Science & Technology*, *8*(7), 184–192. https://doi.org/10.46243/jst.2023.v8.i07.pp184-192

⬇ text Italics are shown as *asterisks* in plain text — the journal or book title and the volume.

BibTeX

@article{syedsalmanhussain2023identifying,
  author    = {Syed Salman Hussain, Syed Salman Hussain},
  title     = {{IDENTIFYING AND PREVENTING THE DISSEMINATION OF FAKE NEWS}},
  journal   = {Journal of Science \& Technology},
  year      = {2023},
  month     = {aug},
  volume    = {8},
  number    = {7},
  pages     = {184--192},
  publisher = {Longman Publishers},
  issn      = {2456-5660},
  doi       = {10.46243/jst.2023.v8.i07.pp184-192},
  url       = {https://doi.org/10.46243/jst.2023.v8.i07.pp184-192},
  language  = {en},
  abstract  = {Misinformation poses a significant threat to democratic societies, particularly in today’s interconnected digital world, as it has the potential to shape public opinion. Researchers from various disciplines, including computer science, political science, information science, and linguistics, have been investigating the spread of fake news, methods for detecting it, and strategies to mitigate its impact. However, effectively identifying and preventing the dissemination of false information remains a complex endeavor. Given the increasing role of Artificial Intelligence (AI) systems, it is vital to offer clear and user – ,bfriendly explanations for the decisions made by fake news detectors, particularly on social media platforms. Therefore, this paper conducts a systematic analysis of the latest approaches employed to detect and combat the spread of fake news. By examining these approaches, we uncover key challenges and propose potential future research directions, with a particular emphasis on integrating AI explain ability into fake news credibility systems}
}

⬇ .bib

RIS (EndNote, Zotero, Mendeley)

TY  - JOUR
TI  - IDENTIFYING AND PREVENTING THE DISSEMINATION OF FAKE NEWS
AU  - Syed Salman Hussain, Syed Salman Hussain
JO  - Journal of Science & Technology
PY  - 2023
DA  - 2023/08/07/
VL  - 8
IS  - 7
SP  - 184
EP  - 192
PB  - Longman Publishers
SN  - 2456-5660
LA  - en
AB  - Misinformation poses a significant threat to democratic societies, particularly in today’s interconnected digital world, as it has the potential to shape public opinion. Researchers from various disciplines, including computer science, political science, information science, and linguistics, have been investigating the spread of fake news, methods for detecting it, and strategies to mitigate its impact. However, effectively identifying and preventing the dissemination of false information remains a complex endeavor. Given the increasing role of Artificial Intelligence (AI) systems, it is vital to offer clear and user – ,bfriendly explanations for the decisions made by fake news detectors, particularly on social media platforms. Therefore, this paper conducts a systematic analysis of the latest approaches employed to detect and combat the spread of fake news. By examining these approaches, we uncover key challenges and propose potential future research directions, with a particular emphasis on integrating AI explain ability into fake news credibility systems
DO  - 10.46243/jst.2023.v8.i07.pp184-192
UR  - https://doi.org/10.46243/jst.2023.v8.i07.pp184-192
ER  -

⬇ .ris

CSL-JSON

{
    "type": "article-journal",
    "id": "10.46243/jst.2023.v8.i07.pp184-192",
    "DOI": "10.46243/jst.2023.v8.i07.pp184-192",
    "URL": "https://doi.org/10.46243/jst.2023.v8.i07.pp184-192",
    "title": "IDENTIFYING AND PREVENTING THE DISSEMINATION OF FAKE NEWS",
    "source": "Smart Scholars DOI Registry",
    "container-title": "Journal of Science & Technology",
    "author": [
        {
            "family": "Syed Salman Hussain",
            "given": "Syed Salman Hussain"
        }
    ],
    "issued": {
        "date-parts": [
            [
                2023,
                8,
                7
            ]
        ]
    },
    "volume": "8",
    "issue": "7",
    "page": "184-192",
    "publisher": "Longman Publishers",
    "language": "en",
    "abstract": "Misinformation poses a significant threat to democratic societies, particularly in today’s interconnected digital world, as it has the potential to shape public opinion. Researchers from various disciplines, including computer science, political science, information science, and linguistics, have been investigating the spread of fake news, methods for detecting it, and strategies to mitigate its impact. However, effectively identifying and preventing the dissemination of false information remains a complex endeavor. Given the increasing role of Artificial Intelligence (AI) systems, it is vital to offer clear and user – ,bfriendly explanations for the decisions made by fake news detectors, particularly on social media platforms. Therefore, this paper conducts a systematic analysis of the latest approaches employed to detect and combat the spread of fake news. By examining these approaches, we uncover key challenges and propose potential future research directions, with a particular emphasis on integrating AI explain ability into fake news credibility systems",
    "ISSN": "2456-5660"
}

⬇ .json What citeproc and reference managers read; the DOI system hands it out for Accept: application/vnd.citationstyles.csl+json, and so does this registry's resolver.

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