Business Applications in Social Media Analytics

Business Applications in Social Media Analytics

Himani Bansal (Jaypee University, Solan, India) and Gulshan Shrivastava (National Institute of Technology, Patna, India)
Projected Release Date: October, 2021|Copyright: © 2022 |Pages: 330
DOI: 10.4018/978-1-7998-5046-5
ISBN13: 9781799850465|ISBN10: 1799850463|EISBN13: 9781799850472|ISBN13 Softcover: 9781799881223
Out of print.
Description & Coverage

Analytics is not only a buzzword but a catalyst in the up-scaling of businesses. Analytics are essentially a systematic and scientific analysis of the subject area coupled with principles from computer science, mathematics, and statistics. Analytics aim at not only analyzing existing data, but can also predict and forecast, thus accelerating the speed at which business can be driven. The biggest challenge lies not only in analyzing existing data but pre-processing or data cleaning, especially in the case of big data. Sometimes, the data available may not be authentic, therefore verifying accurate characteristics of it is quite challenging. This is certainly a concern when data involved is garnered from social media. The vast data present on social media is unstructured in nature, which makes verification one of the biggest challenges.

Business Applications in Social Media Analytics provides insights detailing every aspect of the field of business applications analytics, specifically social media analytics. The chapters will present analyses of business applications on social media and will highlight the most debated aspects of the field while adding to the knowledge enrichment in this subject matter. The chapters will address different aspects such as sarcasm detection, issues in data consolidation, dependability and trust analytics, automation of content extraction, and an assortment of business applications in social media analytics using machine learning, evolutionary algorithms, and other techniques. This book is ideal for managers, social media analysts, data scientists, security analysts, IT specialists, professionals, academicians, students, and researchers working in the field of business analytics, big data, social network data, computer science, analytical engineering, and forensic analysis.


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

  • Behavior Analysis
  • Big Data
  • Business Applications
  • Data Analytics
  • Data Mining
  • Decision Support and Optimization
  • Evolutionary Algorithms
  • Forensic Analysis
  • Online Trust Evaluation
  • Sentimental Analysis
  • Social Network of Things
  • Social Networking Data
  • Social Networks
Table of Contents
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