Essays about: "fake news classification"

Showing result 1 - 5 of 9 essays containing the words fake news classification.

  1. 1. A Preliminary Observation: Can One Linguistic Feature Be the Deterministic Factor for More Accurate Fake News Detection?

    University essay from Uppsala universitet/Institutionen för lingvistik och filologi

    Author : Yini Chen; [2023]
    Keywords : Fake news detection; Generative models;

    Abstract : This study inspected three linguistic features, specifically the percentage of nouns per sentence, the percentage of verbs per sentence, as well as the mean of dependency distance of the sentence, and observed their respective influence on the fake news classification accuracy. In comparison to the previous studies where linguistic features are combined as a set to be leveraged, this study attempted to untangle the effective individual features from the previously proposed optimal sets. READ MORE

  3. 2. Can Large Language Models Enhance Fake News Detection? : Improving Fake News Detection With Data Augmentation

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Emil Ahlbäck; Max Dougly; [2023]
    Keywords : ;

    Abstract : In recent years, the proliferation of fake news has become a significant concern due to its potential to cause harm and sow discord in societies worldwide. To address this issue, machine learning techniques have been employed in a task referred to as fake news detection (FND) to assess the veracity of textual news content. READ MORE

  4. 3. Machine learning and Neural networks in Fake news detection : A mapping study

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Theodor Kudryk; Astrid Lindh; [2022]
    Keywords : Fake news; Information disorder; Detection; Disinformation; Natural Lan-guage Processing; Machine Learning; Neural Networks; Fake news; Desinformation; Detektion; Natural Language Processing; Maskininlärning; Neurala Nätver;

    Abstract : Fake news, or information disorder, is a societal problem that could be partially remedied by automatic detection tools. While still a young research field many such tools have been proposed in academic writing. READ MORE

  5. 4. Data Fusion and Text Mining for Supporting Journalistic Work

    University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

    Author : Vermes Zsombor; [2022]
    Keywords : text mining; data fusion; algorithmic journalism; computational journalism; keyword extraction; named entity recognition; sentiment analysis; fake news classification;

    Abstract : During the past several decades, journalists have been struggling with the ever growing amount of data on the internet. Investigating the validity of the sources or finding similar articles for a story can consume a lot of time and effort. These issues are even amplified by the declining size of the staff of news agencies. READ MORE

  6. 5. All Negative on the Western Front: Analyzing the Sentiment of the Russian News Coverage of Sweden with Generic and Domain-Specific Multinomial Naive Bayes and Support Vector Machines Classifiers

    University essay from Uppsala universitet/Institutionen för lingvistik och filologi

    Author : David Michel; [2021]
    Keywords : sentiment analysis; news sentiment; text classification; cross-domain sentiment classification; domain specificity; domain-transfer problem; transfer learning; knowledge transfer; support vector machines; SVM; multinomial naive Bayes; Sweden; Aurora 17; Russia; Russian news; RT; Sputnik; cyberwarfare; influence campaign; disinformation; fake news; propaganda;

    Abstract : This thesis explores to what extent Multinomial Naive Bayes (MNB) and Support Vector Machines (SVM) classifiers can be used to determine the polarity of news, specifically the news coverage of Sweden by the Russian state-funded news outlets RT and Sputnik. Three experiments are conducted. READ MORE