自动内容分析中的分类错误会导致回归偏差。我们能解决这个问题吗？是的，我们能！

IF 6.3 1区文学 Q1 COMMUNICATION

Communication Methods and Measures Pub Date : 2024-01-16 DOI:10.1080/19312458.2023.2293713

Nathan TeBlunthuis, Valerie Hase, Chung-Hong Chan

引用次数: 0

摘要

自动分类器（AC）通常是通过有监督机器学习（SML）建立的，可以对从文本到图像和视频的大量统计功能强大的数据样本进行分类。它们已成为 ...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Misclassification in Automated Content Analysis Causes Bias in Regression. Can We Fix It? Yes We Can!

Automated classifiers (ACs), often built via supervised machine learning (SML), can categorize large, statistically powerful samples of data ranging from text to images and video. They have become ...

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来源期刊

Communication Methods and Measures COMMUNICATION-

CiteScore

21.10

自引率

1.80%

发文量

期刊介绍： Communication Methods and Measures aims to achieve several goals in the field of communication research. Firstly, it aims to bring attention to and showcase developments in both qualitative and quantitative research methodologies to communication scholars. This journal serves as a platform for researchers across the field to discuss and disseminate methodological tools and approaches. Additionally, Communication Methods and Measures seeks to improve research design and analysis practices by offering suggestions for improvement. It aims to introduce new methods of measurement that are valuable to communication scientists or enhance existing methods. The journal encourages submissions that focus on methods for enhancing research design and theory testing, employing both quantitative and qualitative approaches. Furthermore, the journal is open to articles devoted to exploring the epistemological aspects relevant to communication research methodologies. It welcomes well-written manuscripts that demonstrate the use of methods and articles that highlight the advantages of lesser-known or newer methods over those traditionally used in communication. In summary, Communication Methods and Measures strives to advance the field of communication research by showcasing and discussing innovative methodologies, improving research practices, and introducing new measurement methods.