All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Comparison of fake and real news based on morphological analysis

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F20%3A39916682" target="_blank" >RIV/00216275:25410/20:39916682 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S1877050920312394" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1877050920312394</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.procs.2020.04.247" target="_blank" >10.1016/j.procs.2020.04.247</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Comparison of fake and real news based on morphological analysis

  • Original language description

    Easy access to information results in the phenomenon of false news spreading intentionally through social networks to manipulate people&apos;s opinions. Fake news detection has recently attracted growing interest from the general public and researchers. The paper deals with the morphological analysis of two datasets containing 28 870 news articles. The results were verified using the third dataset consisting of 402 news articles. The analysis of the datasets was carried out using lemmatization and POS tagging. The morphological analysis as a process of classifying the words into grammatical-semantic classes and assigning grammatical categories to these words. Individual words from articles were annotated and statistically significant differences were examined between the classes found in fake and real news articles. The results of the analysis show that statistically significant differences are mainly in the verbs and nouns word classes. Finding statistically significant differences in individual categories of word classes is an important piece of information for the future fake news classifier in terms of selecting appropriate variables for the classification.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Procedia Computer Science : Third International Conference on Computing and Network Communications (CoCoNet&apos;19)

  • ISBN

  • ISSN

    1877-0509

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    2285-2293

  • Publisher name

    Elsevier Science BV

  • Place of publication

    Amsterdam

  • Event location

    Trivadrum

  • Event date

    Dec 18, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article