Intersection of machine learning and computational social sciences /

The text employs computational techniques and large-scale data analysis to study complex social phenomena and human behavior. It discusses diverse methodologies, including agent-based modeling, network analysis, natural language processing, and machine learning, to gain insights into topics ranging...

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Bibliographic Details
Corporate Author:	Taylor & Francis
Other Authors:	Khanday, Akib Mohi Ud Din (Editor), Bouktif, Salah (Editor), Wajid, Mohd (Editor), Rabani, Syed Tanzeel (Editor)
Format:	eBook
Language:	English
Published:	Boca Raton : CRC Press, 2026.
Series:	Future generation information systems
Subjects:	Machine learning. Social sciences > Data processing. Artificial intelligence. Apprentissage automatique. Intelligence artificielle. Sciences sociales > Informatique. artificial intelligence. Machine learning Social sciences > Data processing Electronic books.
Online Access:	Connect to the full text of this electronic book

Description
Summary:	The text employs computational techniques and large-scale data analysis to study complex social phenomena and human behavior. It discusses diverse methodologies, including agent-based modeling, network analysis, natural language processing, and machine learning, to gain insights into topics ranging from social network dynamics and opinion formation to economic trends and public health crises.Features: Discusses the theoretical background of each algorithm in detail and presents the applications of each method. Presents artificial intelligence implications, sustainable artificial intelligence, and the importance of artificial intelligence in agriculture, and energy. Explains the use of predictive modeling in computational social science and applications of computational social science. Showcases the framework for social network analysis, application program interface, data collection methods, and data preprocessing. Covers topics such as density-based spatial clustering of applications with noise, the role of clustering in computational social science, and clustering in network structure. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.
Physical Description:	1 online resource (356 pages) : illustrations (black and white).
ISBN:	9781040902035 1040902030 9781040901977 1040901972 9781003766902 1003766900