Publication result detail

Detection of Fake News Using a Machine Learning Approach

JANKOVÁ, Z.; PÁLEŠ, M.; POTRYKUS, M.; BUICS, L.

Original Title

Detection of Fake News Using a Machine Learning Approach

English Title

Detection of Fake News Using a Machine Learning Approach

Type

Peer-reviewed article not indexed in WoS or Scopus

Original Abstract

The tremendous rise of artificial intelligence and the use of ChatGPT enables the unprecedented rapid spread of various messages. The fundamental problem at present is the spread of false, unverified news and information known as fake news. This great challenge of the modern world causes deliberate manipulation of public opinion, can contribute to the loss of value in the stock market and poses many risks on a global level.

English abstract

The tremendous rise of artificial intelligence and the use of ChatGPT enables the unprecedented rapid spread of various messages. The fundamental problem at present is the spread of false, unverified news and information known as fake news. This great challenge of the modern world causes deliberate manipulation of public opinion, can contribute to the loss of value in the stock market and poses many risks on a global level.

Keywords

fake news; false information; financial market; stock market; social media; SVM; ML

Key words in English

fake news; false information; financial market; stock market; social media; SVM; ML

Authors

JANKOVÁ, Z.; PÁLEŠ, M.; POTRYKUS, M.; BUICS, L.

Released

13.12.2024

Publisher

Brno University of Technology, Faculty of Business and Management,, Czech Republic

Location

Brno

ISBN

1802-8527

Periodical

Trendy ekonomiky a managementu

Volume

42

Number

18

State

Czech Republic

Pages from

81

Pages to

94

Pages count

13

URL

https://trends.fbm.vutbr.cz/index.php/trends/article/view/686

BibTex

@article{BUT193645,
  author="Zuzana {Janková} and Michal {Páleš} and Marcin {Potrykus} and László {Buics}",
  title="Detection of Fake News Using  a Machine Learning Approach",
  journal="Trendy ekonomiky a managementu",
  year="2024",
  volume="42",
  number="18",
  pages="81--94",
  doi="10.13164/trends.2024.42.81",
  issn="1802-8527",
  url="https://trends.fbm.vutbr.cz/index.php/trends/article/view/686"
}