Shulph Ink
Handbook of Computational Social Science, Volume 2: Data Science, Statistical Modelling, and Machine Learning Methods
Handbook of Computational Social Science, Volume 2: Data Science, Statistical Modelling, and Machine Learning Methods
We can order this item for you. Delivery usually takes about 4 to 6 weeks.
This item is not held in our immediate stock. We will order it for you after checkout.
Estimated delivery: About 4 to 6 weeks
YOU SAVE £18.48
- Condition: Brand new
- UK Delivery times: Usually arrives within 2 - 3 working days
- UK Shipping: Fee starts at £3.89. Subject to product weight & dimension
Bulk ordering. Want 15 or more copies? Get a personalised quote and bigger discounts. Learn more about bulk orders.
Couldn't load pickup availability
- More about Handbook of Computational Social Science, Volume 2: Data Science, Statistical Modelling, and Machine Learning Methods
The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines, outlining key debates in the field, showcasing novel statistical modeling and machine learning methods, and drawing from specific case studies to demonstrate the opportunities and challenges in CSS approaches. It is divided into two volumes written by outstanding, internationally renowned scholars, and focuses on foundations and advances in data science, statistical modeling, and machine learning.
Format: Hardback
Length: 412 pages
Publication date: 05 November 2021
Publisher: Taylor & Francis Ltd
The Handbook of Computational Social Science is a comprehensive and invaluable resource for scholars across a wide range of disciplines. It serves as a comprehensive reference source, outlining key debates and presenting innovative statistical modeling and machine learning methods. The Handbook is divided into two volumes, authored by esteemed scholars from around the world.
In this second volume, the focus is on foundations and advances in data science, statistical modeling, and machine learning. It delves into various critical topics, such as managing large datasets, including record linkage, streaming, and handling missing data. Machine learning, agent-based modeling, statistical modeling, and data quality in relation to digital trace and textual data are explored in depth. Probability, non-probability, and crowdsourced samples are also considered as key areas of focus.
Not only does this volume make significant contributions to the consolidation of this rapidly evolving research field, but it also fosters growth into new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, the Handbook is an essential reading for advanced undergraduates, postgraduates, and researchers engaged with computational methods across the social sciences, as well as those in the scientific and engineering sectors.
By providing a comprehensive overview of the state-of-the-art techniques and applications in computational social science, this Handbook serves as a valuable tool for scholars and practitioners alike. It will undoubtedly contribute to the further development and advancement of this field.
Weight: 960g
Dimension: 246 x 174 (mm)
ISBN-13: 9780367457808
UK and International shipping information
UK and International shipping information
We deliver throughout the United Kingdom and to 128 countries and territories worldwide, including the United States, Australia, Canada, Germany, Spain and France.
