Intersection of Machine Learning and Computational Social Sciences
Fr. 278.00
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Gebundene Ausgabe
Erscheinungsdatum
15.06.2026
Abbildungen
schwarz-weiss Illustrationen, Raster,schwarz-weiss, Zeichnungen, schwarz-weiss, Tabellen, schwarz-weiss
Herausgeber
Akib Mohi Ud Din Khanday + weitereVerlag
Taylor & FrancisSeitenzahl
356
Maße (L/B/H)
23.7/16.2/2.5 cm
Gewicht
718 g
Sprache
Englisch
ISBN
978-1-03-282117-7
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.
- 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.
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