In the era of big data, knowledge about machine learning and artificial intelligence is becoming crucial for communication researchers navigating the landscape of digital media. This book provides foundational knowledge and techniques to empower researchers to leverage ML and AI at the intersection of communication and data science.
In this book, Xiaoqun Zhang argues that acquiring knowledge of machine learning (ML) and artificial intelligence (AI) tools is increasingly imperative for the trajectory of communication research in the era of big data. Rather than simply being a matter of keeping pace with technological advances, Zhang posits that these tools are strategically imperative for navigating the complexities of the digital media landscape and big data analysis, and they provide powerful methodologies empowering researchers to uncover nuanced insights and trends within the vast expanse of digital information. Although this can be a daunting notion for researchers without a formal background in mathematics or computer science, this book highlights the substantial rewards of investing time and effort into the endeavor – mastery of ML and AI not only facilitates more sophisticated big data analyses, but also fosters interdisciplinary collaborations, enhancing the richness and depth of research outcomes. This book will serve as a foundational resource for communication scholars by providing essential knowledge and techniques to effectively leverage ML and AI at the intersection of communication research and data science.
Arvustused
The first comprehensive guide bridging communication research and artificial intelligence, Zhang's work demystifies big data, machine learning, and AI for communication scholars. Through accessible explanations and practical case studies, this book equips researchers with the essential knowledge to leverage state-of-the-art language models and computational tools, even without extensive technical backgrounds. Zhang demonstrates how to apply these emerging technologies to analyze vast datasets from social media and digital platformsa critical skill as communication research evolves in the big data era. With detailed Python code examples and clear guidance on accessing computational resources, this book is an indispensable resource for communication scholars aiming to stay competitive in an AI-driven research landscape. * Ryan Boettger, Professor of Technical Communication, University of North Texas, USA *
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In the era of big data, knowledge about machine learning and artificial intelligence is becoming crucial for communication researchers navigating the landscape of digital media. This book provides foundational knowledge and techniques to empower researchers to leverage ML and AI at the intersection of communication and data science.
Chapter
1. Big Data, Machine Learning, Artificial Intelligence and Communication Studies: An Introduction
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2. Fundamental Concepts, Theories, Models in Big Data, ML, and AI
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3. Natural Language Processing and ML/AI Models
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4. Big Data, ML, and AI in Communication Studies: A Bibliometric Analysis.
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5. The Application of ML/AI Models in Communication Research: Two Case Studies.
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6. Remain Competitive in Communication Research in the Big Data Era.
Xiaoqun Zhang is associate professor in the Mayborn School of Journalism at University of North Texas.
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