Advanced Applications of NLP and Deep Learning in Social Media Data

Advanced Applications of NLP and Deep Learning in Social Media Data

Indexed In: SCOPUS
Release Date: June, 2023|Copyright: © 2023 |Pages: 303
DOI: 10.4018/978-1-6684-6909-5
ISBN13: 9781668469095|ISBN10: 166846909X|EISBN13: 9781668469118
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Description & Coverage
Description:

Social media platforms are one of the main generators of textual data where people around the world share their daily life experiences and information with online society. The social, personal, and professional lives of people on these social networking sites generate not only a huge amount of data but also open doors for researchers and academicians with numerous research opportunities. This ample amount of data needs advanced machine learning, deep learning, and intelligent tools and techniques to receive, process, and interpret the information to resolve real-life challenges and improve the online social lives of people.

Advanced Applications of NLP and Deep Learning in Social Media Data bridges the gap between natural language processing (NLP), advanced machine learning, deep learning, and online social media. It hopes to build a better and safer social media space by making human language available on different social media platforms intelligible for machines with the blessings of AI. Covering topics such as machine learning-based prediction, emotion recognition, and high-dimensional text clustering, this premier reference source is an essential resource for OSN service providers, psychiatrists, psychologists, clinicians, sociologists, students and educators of higher education, librarians, researchers, and academicians.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Deep Learning Approaches
  • Emotion Recognition
  • High-Dimensional Text Clustering
  • LSTM Network
  • Machine Learning-Based Prediction
  • Memory Architecture
  • Multi-Level Classification
  • Natural Language Processing
  • Social Media
  • Social Spam Campaigns
  • User Involvement
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Editor/Author Biographies
Ahmed A. Abd El-Latif received the B.Sc. degree with honor rank in Mathematics and Computer Science in 2005 and M.Sc. degree in Computer Science in 2010, all from Menoufia University, Egypt. He received his Ph. D. degree in Computer Science & Technology at Harbin Institute of Technology (H.I.T), Harbin, P. R. China in 2013. He is an associate professor of Computer Science at Menoufia University, Egypt. He is author and co-author of more than 130 papers in reputal journal and conferences. He received many awards, State Encouragement Award in Engineering Sciences 2016, Arab Republic of Egypt; the best Ph.D student award from Harbin Institute of Technology, China 2013; Young scientific award, Menoufia University, Egypt 2014. He is a fellow at Academy of Scientific Research and Technology, Egypt. His areas of interests are multimedia content encryption, secure wireless communication, IoT, applied cryptanalysis, perceptual cryptography, secret media sharing, information hiding, biometrics, forensic analysis in digital images, and quantum information processing. Dr. Abd El-Latif is an associate editor of Journal of Cyber Security and Mobility, and Mathematical Problems in Engineering.

Mohammed A. El-Affendi is currently a Professor of computer science with the Department of Computer Science, Prince Sultan University, the Former Dean of CCIS, AIDE, the Rector, the Founder, and the Director of the Data Science Laboratory (EIAS), and the Founder and the Director of the Center of Excellence in CyberSecurity. His current research interests include data science, intelligent and cognitive systems, machine learning, and natural language processing.

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