Data Analytics for Social Microblogging Platforms

Soumi Dutta works in the Institute of Engineering and Management, Kolkata, West Bengal, India. Asit Kumar Das is Professor of Computer Science and Technology, at the Indian Institute of Engineering Science and Technology Shibpur, Howrah. He is also the Head of the Center of Healthcare Science and Technology of the Institute. His area of research interest includes data mining and pattern recognition, social networks, bioinformatics, machine learning and soft computing, text, audio and video data analysis. Dr. Ghosh is an Assistant Professor in the Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, India. His primary research interests are in social network analysis, legal data analytics, and algorithmic bias and fairness. His research uses techniques from machine learning, natural language processing, information retrieval, and complex network theory. He received his PhD in Computer Science from IIT Kharagpur in 2013. He is a Humboldt Post-doctoral research fellow at the Max Planck Institute for Software Systems (MPI-SWS), Germany. He has also been an Assistant Professor at the Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Shibpur, India. Debabrata Samanta is the Department Chair and Assistant Professor at the Department of Computing and Information Technologies, Rochester Institute of Technology—RIT Tirana, Tirana, Albania. He obtained his Ph.D. in Computer Science and Engg. in the area of SAR Image Processing. He is keenly interested in Interdisciplinary Research and development and has experience spanning fields of SAR Image Analysis, Video surveillance, a Heuristic algorithm for Image Classification, Deep Learning Framework for Detection and Classification, Blockchain, Statistical Modelling, Wireless Adhoc Networks, Natural Language Processing. He has successfully completed six Consultancy Projects. He owns 22 Patents (4 Design Indian Patents and 2 Australian patents Granted, 16 Indian Patents published) and 2 copyrights. He has authored or co-authored over 224 research papers; he has co-authored 13 books and co-edited 13 books. He has presented various papers at international conferences and received Best Paper awards. He is an IEEE Senior Member, an Associate Life Member of the Computer Society of India (CSI), and a Life Member of the Indian Society for Technical Education (ISTE).

• Section 1: Introduction of Intelligent Information Filtering and Organisation Systems for Social Microblogging Sites1. Introduction to Microblogging Sites2. Data structures and data storage3. Data Collection using Twitter APISection 2: Microblogging dataset Applications and Implications4. Brief overview of existing algorithms and ApplicationsAttribute Selection Methods - Filter Method, Wrapper Method, Other attribute selection algorithms5. Spam detection - Spam detection in OSM - Attribute selection for spam detection6.  Summarization - Automatic Document Summarization, Summarization of microblogs, Comparing algorithms for microblog summarization, Summarization Validation7. Cluster Analysis, Clustering Algorithms, Partition based Clustering, Hierarchical Clustering, Density-based Clustering, Graph clustering algorithms, Cluster Validation Indices, Clustering in Online Social Microblogging SitesSection 3: Attribute Selection to Improve Spam Classification8. Introduction of Attribute Selection to Improve Spam Classification9. Attribute Selection Based in Basics of Rough Set Theory and Attribute selection algorithm.10. Experimental Dataset Description11. Evaluating performance and Evaluation measures12. Fake news, scams, recruiting by terrorist or criminal organizationsSection 4: Microblog Summarization13. Introduction of Microblog Summarization14. Base summarization algorithms15. Unsupervised ensemble summarization approach16. Supervised ensemble summarisation approach17. Experiments and results and Performance analysis18. Demonstrating summarization examplesSection 5: Microblog Clustering19. Introduction of Microblog ClusteringExperimental Dataset - will be posted on Mendeley and link included at end of Chapter 1920. Graph Based Clustering Technique21. Genetic Algorithm based Clustering22. Clustering based on Feature Selection23. Clustering Microblogs using Dimensionality Reduction24. Evaluating performance and result AnalysisSection 6: Conclusion and Future Directions on Social Microblogging Sites