Data Mining Approaches for Big Data and Sentiment Analysis in Social Media - Rilegato

Rilegato

ISBN 10: 1799884139 ISBN 13: 9781799884132

Casa editrice: Engineering Science Reference, 2021

Riassunto

Social media sites are constantly evolving with huge amounts of scattered data or big data, which makes it difficult for researchers to trace the information flow. It is a daunting task to extract a useful piece of information from the vast unstructured big data; the disorganized structure of social media contains data in various forms such as text and videos as well as huge real-time data on which traditional analytical methods like statistical approaches fail miserably. Due to this, there is a need for efficient data mining techniques that can overcome the shortcomings of the traditional approaches.

Data Mining Approaches for Big Data and Sentiment Analysis in Social Media encourages researchers to explore the key concepts of data mining, such as how they can be utilized on online social media platforms, and provides advances on data mining for big data and sentiment analysis in online social media, as well as future research directions. Covering a range of concepts from machine learning methods to data mining for big data analytics, this book is ideal for graduate students, academicians, faculty members, scientists, researchers, data analysts, social media analysts, managers, and software developers who are seeking to learn and carry out research in the area of data mining for big data and sentiment.

Dettagli dell?edizione

• Editore: Engineering Science Reference
• Data di pubblicazione: 2021
• ISBN 10: 1799884139
• ISBN 13: 9781799884132
• Rilegatura: Copertina rigida
• Lingua: Inglese
• Numero di pagine: 330
• Redattore: Gupta Brij B., Perakovic Dragan, El-latif Ahmed A. Abd, Gupta Deepak
• Contatto del produttore: non disponibile