A Survey for News Credibility in Social Networks
Author:
Affiliation:
1. Faculty of Commerce and Business Administration, Helwan University, Egypt
2. Helwan University, Egypt
3. Faculty of Computers and Information Technology, Future University in Egypt, Egypt
Abstract
Text mining has been a vital area that has been linked to some fields of research such as machine learning, data analysis and gathering, and information recovery. To extract knowledge and information, Natural Language Processing (NLP) was used alternative techniques. Text mining analyses unstructured data to provide critical data and information plans in a timely manner. Nowadays everyone uses online communication activities to keep in touch with others in their daily life. As a result, they're a great way to connect. Not sorting in a paragraph in a format suitable for word recognition has become a point of contention. intensity can cause a variety of inconsistencies, such as lexical, semantic, linguistic, and syntactic ambiguities, determining the proper data arrangement. Information and data are required for learning things and reaching knowledge. This paper covered how to use text mining to determine the credibility of news on social media. The findings of this study could be used as the basis for future text mining research.
Publisher
IGI Global
Subject
Computer Networks and Communications,Computer Science Applications
Reference70 articles.
1. A Review of Towered Big-Data Service Model for Biomedical Text-Mining Databases.;A.Abed;International Journal of Advanced Computer Science and Applications,2017
2. User-Generated Content (UGC) Credibility on Social Media Using Sentiment Classification.;E.Afify;FCI-H Informatics Bulletin,2019
3. Albahar, M. (2021). A hybrid model for fake news detection: Leveraging news content and user comments in fake news. The Institution of Engineering and Technology, 9.
4. Web mining for innovation ecosystem mapping: A framework and a large‑scale pilot study.;J.Axenbeck;Scientometrics,2020
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