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Cite this DOI

10.46243/jst.2023.v8.i04.pp32-39 · DNN based fake news identification and analysis

APA (7th edition)

Dr.S.Suresh, D. (2023). DNN based fake news identification and analysis. *Journal of Science & Technology*, *8*(4), 32–39. https://doi.org/10.46243/jst.2023.v8.i04.pp32-39

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

BibTeX

@article{drssuresh2023based,
  author    = {Dr.S.Suresh, Dr.S.Suresh},
  title     = {{DNN based fake news identification and analysis}},
  journal   = {Journal of Science \& Technology},
  year      = {2023},
  month     = {oct},
  volume    = {8},
  number    = {4},
  pages     = {32--39},
  publisher = {Longman Publishers},
  issn      = {2456-5660},
  doi       = {10.46243/jst.2023.v8.i04.pp32-39},
  url       = {https://doi.org/10.46243/jst.2023.v8.i04.pp32-39},
  language  = {en},
  abstract  = {In this project we show an approach for detecting fake statements made by public figures by means of artificial intelligence. Several approaches were implemented as a software system and tested against a data set of statements. The best achieved result in binary classification problem (true or false statement) is 86\%. The results may be improved in several ways that are described in the article as well. The progress in modern informational technologies brings us to the era where information is as accessible as ever. It is possible to find the answers to the questions we are interested in a matter of seconds. Availability of mobile devices makes it even more convenient for the users. This factor changed the way of how people get the news information a lot. Every mainstream mass media has its own online portal, Facebook account, Twitter account etc., so people can access news information really quickly}
}

⬇ .bib

RIS (EndNote, Zotero, Mendeley)

TY  - JOUR
TI  - DNN based fake news identification and analysis
AU  - Dr.S.Suresh, Dr.S.Suresh
JO  - Journal of Science & Technology
PY  - 2023
DA  - 2023/10/04/
VL  - 8
IS  - 4
SP  - 32
EP  - 39
PB  - Longman Publishers
SN  - 2456-5660
LA  - en
AB  - In this project we show an approach for detecting fake statements made by public figures by means of artificial intelligence. Several approaches were implemented as a software system and tested against a data set of statements. The best achieved result in binary classification problem (true or false statement) is 86%. The results may be improved in several ways that are described in the article as well. The progress in modern informational technologies brings us to the era where information is as accessible as ever. It is possible to find the answers to the questions we are interested in a matter of seconds. Availability of mobile devices makes it even more convenient for the users. This factor changed the way of how people get the news information a lot. Every mainstream mass media has its own online portal, Facebook account, Twitter account etc., so people can access news information really quickly
DO  - 10.46243/jst.2023.v8.i04.pp32-39
UR  - https://doi.org/10.46243/jst.2023.v8.i04.pp32-39
ER  -

⬇ .ris

CSL-JSON

{
    "type": "article-journal",
    "id": "10.46243/jst.2023.v8.i04.pp32-39",
    "DOI": "10.46243/jst.2023.v8.i04.pp32-39",
    "URL": "https://doi.org/10.46243/jst.2023.v8.i04.pp32-39",
    "title": "DNN based fake news identification and analysis",
    "source": "Smart Scholars DOI Registry",
    "container-title": "Journal of Science & Technology",
    "author": [
        {
            "family": "Dr.S.Suresh",
            "given": "Dr.S.Suresh"
        }
    ],
    "issued": {
        "date-parts": [
            [
                2023,
                10,
                4
            ]
        ]
    },
    "volume": "8",
    "issue": "4",
    "page": "32-39",
    "publisher": "Longman Publishers",
    "language": "en",
    "abstract": "In this project we show an approach for detecting fake statements made by public figures by means of artificial intelligence. Several approaches were implemented as a software system and tested against a data set of statements. The best achieved result in binary classification problem (true or false statement) is 86%. The results may be improved in several ways that are described in the article as well. The progress in modern informational technologies brings us to the era where information is as accessible as ever. It is possible to find the answers to the questions we are interested in a matter of seconds. Availability of mobile devices makes it even more convenient for the users. This factor changed the way of how people get the news information a lot. Every mainstream mass media has its own online portal, Facebook account, Twitter account etc., so people can access news information really quickly",
    "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.

From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjst.2023.v8.i04.pp32-39 gives all four in one JSON answer.

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