Reviews are integral to e-commerce services and products. They contain a wealth of information about the opinions and experiences of users, which can help better understand consumer decisions and improve user experience with products and services. Today, data scientists analyze reviews by developing rules and models to extract, aggregate, and understand information embedded in the review text. However, working with thousands of reviews, which are typically noisy incomplete text, can be daunting without proper tools. Here we first contribute results from an interview study that we conducted with fifteen data scientists who work with review text, providing insights into their practices and challenges. Results suggest data scientists need interactive systems for many review analysis tasks. In response we introduce Teddy, an interactive system that enables data scientists to quickly obtain insights from reviews and improve their extraction and modeling pipelines.

中文翻译：

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Teddy：交互式评论分析系统

评论是电子商务服务和产品不可或缺的一部分。它们包含有关用户意见和体验的丰富信息，可以帮助更好地了解消费者的决策并改善用户对产品和服务的体验。今天，数据科学家通过开发规则和模型来分析评论，以提取、汇总和理解评论文本中嵌入的信息。但是，如果没有适当的工具，处理数千条评论（通常是嘈杂的不完整文本）可能会令人生畏。在这里，我们首先提供了一项访谈研究的结果，该研究与 15 位数据科学家一起使用评论文本，提供了对他们的实践和挑战的见解。结果表明，数据科学家需要交互式系统来完成许多评论分析任务。作为回应，我们推出了泰迪，