Data Analytics for Social Microblogging Platforms 1st Edition by Soumi Dutta 0323972307 9780323972307

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ISBN-10 :  0323972307 

ISBN-13 : 9780323972307

Author:  Soumi Dutta 

Data Analysis for Social Microblogging Platforms explores the nature of microblog datasets, also covering the larger field which focuses on information, data and knowledge in the context of natural language processing. The book investigates a range of significant computational techniques which enable data and computer scientists to recognize patterns in these vast datasets, including machine learning, data mining algorithms, rough set and fuzzy set theory, evolutionary computations, combinatorial pattern matching, clustering, summarization and classification. Chapters focus on basic online micro blogging data analysis research methodologies, community detection, summarization application development, performance evaluation and their applications in big data.

Data Analytics for Social Microblogging Platforms 1st Table of contents:

Part 1: Introduction of intelligent information filtering and organization systems for social microblogging sites
Chapter 1: Introduction to microblogging sites
Abstract
1.1. Introduction
1.2. Online social networking sites
1.3. Advantages and disadvantages of social networking
1.4. Microblogging sites
1.5. Information of social microblogging sites
1.6. Challenges in using microblogging sites
1.7. Background of the Twitter microblogging site
1.8. Motivation of research
1.9. Challenges and requirements of multi-document summarization
1.10. Contributions of this research
1.11. Conclusion
References
Chapter 2: Literature review on data analytics for social microblogging platforms
Abstract
2.1. Introduction
2.2. Attribute selection and its application in spam detection
2.3. Summarization with various methods
2.4. Cluster analysis of microblogs
2.5. Conclusion
References
Chapter 3: Data collection using Twitter API
Abstract
3.1. Introduction
3.2. Experimental dataset description
3.3. Data preprocessing
3.4. Removal of user names and URLs
3.5. Converting emojis and emoticons to words
3.6. Conclusion
References
Part 2: Microblogging dataset applications and implications
Chapter 4: Attribute selection to improve spam classification
Abstract
4.1. Introduction
4.2. Literature survey
4.3. Methodology for classification
4.4. Experimental dataset
4.5. Evaluating performance
4.6. Conclusion
References
Chapter 5: Ensemble summarization algorithms for microblog summarization
Abstract
5.1. Introduction
5.2. Base summarization algorithms
5.3. Unsupervised ensemble summarization
5.4. Supervised ensemble summarization
5.5. Experiments and results
5.6. Demonstrating the input and output of summarization algorithms through an example
5.7. Conclusion
References
Chapter 6: Graph-based clustering technique for microblog clustering
Abstract
6.1. Introduction
6.2. Related work
6.3. Background studies
6.4. Proposed methodology
6.5. Results and discussion
6.6. Conclusion
References
Chapter 7: Genetic algorithm-based microblog clustering technique
Abstract
7.1. Introduction
7.2. Related work
7.3. Clustering using genetic algorithms and K-means
7.4. Evaluating performance
7.5. Experimental dataset
7.6. Conclusion
References
Part 3: Attribute selection to improve spam classification
Chapter 8: Feature selection-based microblog clustering technique
Abstract
8.1. Introduction
8.2. Related work
8.3. Microblog clustering algorithms
8.4. Dataset for clustering algorithms
8.5. Experimental results
8.6. Conclusion
References
Chapter 9: Dimensionality reduction techniques in microblog clustering models
Abstract
9.1. Introduction
9.2. Literature survey
9.3. Proposed methodology
9.4. Dataset
9.5. Results and discussion
9.6. Conclusion
References
Chapter 10: Conclusion and future directions
Abstract
10.1. Introduction
10.2. Summary of contributions
10.3. Future research directions

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Tags: Data Analytics, Social Microblogging, Platforms, Soumi Dutta