Results 21 to 30 of about 346,740 (322)

A Survey of Detection and Mitigation for Fake Images on Social Media Platforms

open access: yesApplied Sciences, 2023
Recently, the spread of fake images on social media platforms has become a significant concern for individuals, organizations, and governments. These images are often created using sophisticated techniques to spread misinformation, influence public ...
Dilip Kumar Sharma   +5 more
doaj   +1 more source

Online Fake Review Detection Using Supervised Machine Learning And BERT Model [PDF]

open access: yesarXiv.org, 2023
Online shopping stores have grown steadily over the past few years. Due to the massive growth of these businesses, the detection of fake reviews has attracted attention.
Abrar Qadir Mir, F. Khan, M. Chishti
semanticscholar   +1 more source

A Review of Methodologies for Fake News Analysis

open access: yesIEEE Access, 2023
Nowadays, with the proliferation of different news sources, fake news detection is becoming a crucial topic to research. Millions of articles are published daily in the press, on social media, and in electronic media, and many of them may be fake.
Mehedi Tajrian   +3 more
doaj   +1 more source

An Ensemble Model for Fake Online Review Detection Based on Data Resampling, Feature Pruning, and Parameter Optimization

open access: yesIEEE Access, 2021
With the widespread of fake online reviews, the detection of fake reviews has become a hot research issue. Despite the efforts of existing studies on fake review detection, the issues of imbalanced data and feature pruning still lack sufficient attention.
Jianrong Yao, Yuan Zheng, Hui Jiang
doaj   +1 more source

Fake Review Detection using Machine Learning

open access: yesComputational Intelligence and Machine Learning, 2023
Online reviews have become increasingly important in the world of e-commerce, serving as a powerful tool to establish a business's reputation and attract new customers. However, the rise of fake reviews has become a growing concern as they can skew the reputation of a business and deceive potential customers.
Gayathri M   +2 more
  +4 more sources

Fame for sale: efficient detection of fake Twitter followers [PDF]

open access: yes, 2015
$\textit{Fake followers}$ are those Twitter accounts specifically created to inflate the number of followers of a target account. Fake followers are dangerous for the social platform and beyond, since they may alter concepts like popularity and influence
Cresci, Stefano   +4 more
core   +3 more sources

Fake View Analytics in Online Video Services [PDF]

open access: yes, 2013
Online video-on-demand(VoD) services invariably maintain a view count for each video they serve, and it has become an important currency for various stakeholders, from viewers, to content owners, advertizers, and the online service providers themselves ...
Bolton R. J.   +3 more
core   +1 more source

Evaluating the Spread of Fake News and its Detection. Techniques on Social Networking Sites

open access: yesRomanian Journal of Communications and Public Relations, 2020
The phenomenon of fake news has become a much contentious issue recently. The controversy regarding this issue has further been intensified by the openness of social media platforms.
Isyaku Hassan   +2 more
doaj   +1 more source

A Review on Fake News Detection

open access: yesInternational Journal for Research in Applied Science and Engineering Technology, 2023
Abstract: The widespread increase of fake news, generated by both humans and machines, has negative impacts on both society and individuals, politically and socially. The fast-paced nature of social networks makes it difficult to promptly evaluate the reliability of news. Hence, there is a growing need for automated tools to detect fake news.
Adwait Bandal, Tushar Rane
openaire   +1 more source

Fake Reviewer Groups’ Detection System

open access: yesIOSR Journal of Computer Engineering, 2014
We have the cyber space occupied with most of the opinions, comments and reviews. We also see the use of opinions in decision making process of many organizations. Not only organizations use these reviews but also users use them to a great extent. So using this opportunity, many groups try to game this system by providing fake reviews.
Kolhe N.M.   +3 more
openaire   +1 more source

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