Guest Editors
Prof. Jawad Khan
Email: jkhanbk1@gachon.ac.kr
Affiliation: Department of Artificial Intelligence and Software Gachon University, 1342 Seongnamdaero, Sujeong-gu, Seongnam-si 13120, Repulbic of Korea
Homepage:
Research Interests: big data, data mining, opinion mining, sentiment analysis
Prof. Dildar Hussain
Email: hussain.bangash@sejong.ac.kr
Affiliation: Department of Artificial Intelligence and Data Science, Sejong University, Seoul 05006, Republic of Korea
Homepage:
Research Interests: artificial intelligence, machine learning, and deep learning, big data mining
Prof. Inayat Khan
Email: inayatkhan@uetmardan.edu.pk
Affiliation: Department of Computer Science, University of Engineering and Technology, Mardan, 23200, Pakistan
Homepage:
Research Interests: deep learning, ubiquitous computing, accessibility, mining big data
Prof. Shah Khalid
Email: shah.khalid@seecs.edu.pk
Affiliation: School of Electrical Engineering and Computer Science, National University of Sciences and Technology, Islamabad 44000, Pakistan
Homepage:
Research Interests: information retrieval, web search engines, scholarly retrieval systems, recommender systems, knowledge graphs, social web, real-time sentiment analysis, web engineering, text summarization, federated search, and digital libraries
Summary
The rapid expansion of social media has resulted in vast amounts of multimodal data, presenting unique opportunities and challenges for big data and data mining researchers. This special issue focuses on innovative approaches for processing and analyzing this complex data, enabling real-time insights into user sentiment, emerging trends, and public discourse. It aims to highlight cutting-edge research on scalable data architectures, machine learning models, and natural language processing (NLP) techniques for extracting valuable information from high-dimensional, noisy, and rapidly changing social media streams. Key topics include sentiment analysis, data fusion, real-time event detection, and anomaly detection, as well as ethical considerations and practical applications in brand management, customer insights, and decision-making. Researchers are encouraged to submit original research, case studies, and theoretical contributions that address the challenges of social media analytics and advance the field of big data and data mining.
Keywords
big data, data mining, social media analytics, sentiment analysis, machine learning, deep learning, natural language processing, data fusion, real-time analytics, anomaly detection
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