嘉　宾：俞一凡  Associate Professor  The University of Texas at Austin

主持人：宋婷婷  副教授  上海交通大学安泰经济与管理学院

时　间：2024年07月08日（周一）16:00-17:30

地　点：上海交通大学 徐汇校区安泰经济与管理学院A403

内容简介:

Information systems (IS) researchers often use machine learning algorithms to recognize emotions in massive and unstructured online content and then study the causal effect of emotions on various business outcomes. Large language models (LLMs) as automatic emotion analyzers offer new opportunities for IS researchers to advance the causal understanding of emotions. Nevertheless, we show that directly plugging LLM-generated emotional variables into econometric models can induce bias in causal estimation because LLMs are imperfect in emotion recognition, which adds noise to the causal models. We propose a novel algorithm to correct such bias. A key feature is that the algorithm considers predictions generated by different LLMs to form fuzzy interval data. Then, partial identification of causal parameters is achieved. The algorithm meets three design requirements. First, it is unsupervised, meaning it does not need additional labeled data to correct the causal estimation. Second, it is flexible in incorporating the predictions of different LLMs (leveraging the ``wisdom of the AI crowd'') and can be easily adapted to various causal models. Third, the causal estimators are theoretically guaranteed to achieve consistency. This work provides important implications for causal inference with LLMs, the causal study of emotions, and prescriptive analytics for fuzzy interval data.

演讲人简介：

Dr. Yifan Yu is an assistant professor from the Department of Information, Risk, and Operations Management, at McCombs School of Business, The University of Texas at Austin. Dr. Yu obtained his PhD degree from University of Washington. He received bachelor's and master's degrees from Tsinghua University. His research centers on (1) the economics of artificial intelligence and machine learning; (2) business analytics leveraging online unstructured data (i.e., text, images, videos, networks, behavioral sequences). He has published in top journals in the area of Information Systems (ISR and MISQ) and received several best paper awards or nominations at the top Information Systems conferences (e.g., INFORMS, CIST, and WITS).

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