Computational Analysis of Communication

The use of computational analysis is increasing in social science disciplines, such as political science, sociology, psychology, and media studies. Computational Analysis of Communication provides clear guidance on leveraging computational techniques to answer social science questions. It teaches readers how to use state-of-the-art computational methods to perform data-driven analyses of social science issues, with a focus on big data, data visualization, text analysis, predictive analytics, and reproducible social science.

Format: Paperback / softback
Length: 336 pages
Publication date: 03 March 2022
Publisher: John Wiley & Sons Inc

In the realm of social sciences, the integration of computational techniques is gaining significant momentum. Political science, sociology, psychology, and media studies are just a few disciplines that are harnessing the power of statistical modeling, machine learning, and other computational tools to unravel complex questions and gain insights.

The use of computational analysis is transforming the way electoral results are predicted, social sentiment is measured, consumer interest is evaluated, and various other aspects of society are analyzed. By leveraging these advanced methods, researchers and practitioners can gain a deeper understanding of complex phenomena and make more informed decisions.

One textbook that stands out in this field is Computational Analysis of Communication. This accessible textbook is designed to teach social science students and practitioners how to use computational methods in a broad range of applications. It assumes little or no background in data science or computer linguistics, making it suitable for a wide audience.

The book is divided into four parts, each covering a different aspect of computational analysis in social sciences. The first part provides an introduction to the field, discussing the importance of data and the challenges faced in analyzing social science data. The second part covers data gathering and cleaning, emphasizing the importance of accurate and reliable data for accurate analysis. The third part explores statistical and quantitative analysis, introducing readers to various statistical models and techniques for analyzing social science data. The fourth part focuses on data visualization and interpretation, teaching readers how to present and communicate the results of their analysis effectively.

A cross-disciplinary team of authors, with expertise in both the social sciences and computer science, collaborated on the textbook. They explain the concepts and methods in a clear and concise manner, using real-world examples and case studies to illustrate their points. The book also includes sample code in Python, which allows readers to apply the techniques learned in the text to their own research questions and cases.

One of the unique features of Computational Analysis of Communication is its hybrid format. It is available in print, as an ebook, and also as open-access online viewing. This makes it accessible to a wide range of readers, regardless of their location or access to resources. The book is also developed in partnership with various organizations and institutions, ensuring that it stays up-to-date with the latest developments in the field.

In conclusion, Computational Analysis of Communication is a valuable resource for social science students and practitioners who want to leverage computational techniques to answer social science questions. With its clear explanations, practical guidance, and interdisciplinary approach, the book provides a comprehensive introduction to the field. Whether you are a beginner or an experienced researcher, this textbook will help you unlock the power of data and gain insights into the complex world around us.

Weight: 632g
Dimension: 178 x 253 x 24 (mm)
ISBN-13: 9781119680239