Beyond sentiment: an algorithmic strategy for identifying evaluations within large text corpora

IF 6.3 1区 文学 Q1 COMMUNICATION
Maximilian Overbeck, Christian Baden, Tali Aharoni, Eedan Amit-Danhi, Keren Tenenboim-Weinblatt
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引用次数: 1

Abstract

In this paper, we propose a new strategy for classifying evaluations in large text corpora, using supervised machine learning (SML). Departing from a conceptual and methodological critique of the u...
超越情感:在大型文本库中识别评价的算法策略
在本文中,我们提出了一种使用监督机器学习(SML)对大型文本库中的评价进行分类的新策略。我们从概念和方法论角度出发,对使用监督机器学习(SML)的评价方法进行了批判。
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来源期刊
CiteScore
21.10
自引率
1.80%
发文量
9
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.
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