loading
Documents

Research.Publish.Connect.

Paper

Authors: Alvaro Figueira 1 ; Nuno Guimaraes 1 and Luis Torgo 2

Affiliations: 1 CRACS / INESCTEC and University of Porto, Rua do Campo Alegre, Porto and Portugal ; 2 Faculty of Computer Science, Dalhousie University, Halifax and Canada

ISBN: 978-989-758-324-7

Keyword(s): Fake News, Detection Systems, Survey, Next Challenges.

Abstract: Nowadays, false news can be created and disseminated easily through the many social media platforms, resulting in a widespread real-world impact. Modeling and characterizing how false information proliferates on social platforms and why it succeeds in deceiving readers are critical to develop efficient algorithms and tools for their early detection. A recent surge of researching in this area has aimed to address the key issues using methods based on machine learning, deep learning, feature engineering, graph mining, image and video analysis, together with newly created data sets and web services to identify deceiving content. Majority of the research has been targeting fake reviews, biased messages, and against-facts information (false news and hoaxes). In this work, we present a survey on the state of the art concerning types of fake news and the solutions that are being proposed. We focus our survey on content analysis, network propagation, fact-checking and fake news analysis and e merging detection systems. We also discuss the rationale behind successfully deceiving readers. Finally, we highlight important challenges that these solutions bring. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.206.48.142

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Figueira, A.; Guimaraes, N. and Torgo, L. (2018). Current State of the Art to Detect Fake News in Social Media: Global Trendings and Next Challenges.In Proceedings of the 14th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-324-7, pages 332-339. DOI: 10.5220/0007188503320339

@conference{webist18,
author={Alvaro Figueira. and Nuno Guimaraes. and Luis Torgo.},
title={Current State of the Art to Detect Fake News in Social Media: Global Trendings and Next Challenges},
booktitle={Proceedings of the 14th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2018},
pages={332-339},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007188503320339},
isbn={978-989-758-324-7},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Current State of the Art to Detect Fake News in Social Media: Global Trendings and Next Challenges
SN - 978-989-758-324-7
AU - Figueira, A.
AU - Guimaraes, N.
AU - Torgo, L.
PY - 2018
SP - 332
EP - 339
DO - 10.5220/0007188503320339

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.