Can a Humanoid Robot be part of the Organizational Workforce? A User Study Leveraging Sentiment Analysis
원문 초록
Hiring robots for the workplaces is a challenging task as robots have to cater to customer demands, follow organizational protocols and behave with social etiquette. In this study, we propose to have a humanoid social robot, Nadine, as a customer service agent in an open social work environment. The objective of this study is to analyze the effects of humanoid robots on customers at work environment, and see if it can handle social scenarios. We propose to evaluate these objectives through two modes, namely, survey questionnaire and customer feedback. We also propose a novel approach to analyze customer feedback data (text) using sentic computing methods. Specifically, we employ aspect extraction and sentiment analysis to analyze the data. From our framework, we detect sentiment associated to the aspects that mainly concerned the customers during their interaction. This allows us to understand customers expectations and current limitations of robots as employees.
함께 살펴볼 논문
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An Aspect Extraction Framework using Different Embedding Types, Learning Models, and Dependency Structure
PL-FGSA: A Prompt Learning Framework for Fine-Grained Sentiment Analysis Based on MindSpore
From Annotation to Adaptation: Metrics, Synthetic Data, and Aspect Extraction for Aspect-Based Sentiment Analysis with Large Language Models
Learning to Extract Cross-Domain Aspects and Understanding Sentiments Using Large Language Models
Towards a One-stop Solution to Both Aspect Extraction and Sentiment Analysis Tasks with Neural Multi-task Learning
Understanding and Tackling Label Errors in Individual-Level Nature Language Understanding
토론
이 논문과 연결된 포럼 글이 아직 없습니다.