The Computational Content Analyst: Using Machine Learning to Classify Media Messages

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Synopsis
Most digital content, whether it be thousands of news articles or millions of social media posts, is too large for the naked eye alone. Often, the advent of immense datasets requires a more productive approach to labeling media beyond a team of researchers. This book offers practical guidance and Python code to traverse the vast expanses of data—significantly enhancing productivity without compromising scholarly integrity. We’ll survey a wide array of computer-based classification approaches, focusing on easy-to-understand methodological explanations and best practices to ensure that your data is being labeled accurately and precisely. By reading this book, you should leave with an understanding of how to select the best computational content analysis methodology to your needs for the data and problem you have.This guide gives researchers the tools they need to amplify their analytical reach through the integration of content analysis with computational classification approaches, including machine learning and the latest advancements in generative artificial intelligence (AI) and large language models (LLMs). It is particularly useful for academic researchers looking to classify media data and advanced scholars in mass communications research, media studies, digital communication, political communication, and journalism.Complementing the book are online resources: datasets for practice, Python code scripts, extended exercise solutions, and practice quizzes for students, as well as test banks and essay prompts for instructors. Please visit www.routledge.com/9781032846354.
Copyright:
2025

Book Details

Book Quality:
Publisher Quality
ISBN-13:
9781040227206
Related ISBNs:
9781032846309, 9781040227176, 9781003514237, 9781032846354
Publisher:
Taylor & Francis
Date of Addition:
Copyrighted By:
Chris J. Vargo. The right of Chris J. Vargo to be identified as author of this work has been asserted in accordance with sections
Adult content:
No
Language:
English
Has Image Descriptions:
No
Categories:
Nonfiction, Social Studies, Language Arts, Communication
Submitted By:
Bookshare Staff
Usage Restrictions:
This is a copyrighted book.

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