I Gotta Feeling: Advancing Sentiment Analysis in Organizational Science
系统回顾了情感分析在组织科学中的应用，指出研究者常忽视关键决策点，通过实例展示不同选择对结论的影响，并提出五维框架和七条建议来指导方法选择。
Sentiment analysis (SA) has grown considerably in organizational science research over the past two decades, particularly in the last few years. While enthusiasm for integrating advanced natural language processing algorithms is encouraging, authors are not reaping the benefits of such tools fully. Our systematic review of SA application in the organizational sciences suggests that authors struggle to appreciate all of the decisions that are inherent to SA, the choices that are available at each decision point, and the consequences of each choice. To address this gap, we use a working example to illustrate four critical decision points authors confront when conducting SA, and the subsequent impact different choices can have on one's conclusion. Decision points include selecting the SA method, computing a sentiment score, preprocessing the data, and using an appropriate level of analysis. We conclude with a framework outlining five dimensions (e.g., accuracy, interpretability, computational cost) to guide the selection of an SA approach based on study goals and needs, along with seven recommendations to authors wishing to apply SA.