Smarter people analytics with organizational text data: Demonstrations using classic and advanced NLP models
本文演示了如何使用从简单词袋模型到复杂Doc2Vec算法的自然语言处理技术，从组织文本数据中预测公司评分和人格特质，为HRM从业者提供实用指南。
Abstract Recent developments in text mining and natural language processing (NLP) have paved a new way for analysing text data. These techniques are particularly useful for human resource management (HRM) due to the large amount of text information in the field. This paper adds to the literature by introducing and demonstrating steps of using NLP. Two demonstrations are presented: Demonstration One illustrates how simple and straightforward Bag‐of‐Word models applied on textual comments can be used to predict numerical ratings of companies; Demonstration Two shows how personality (self‐reported scores on the Big Five) can be predicted from situational interview questions through more complex Doc2Vec algorithms. Together, these demonstrations show that both simple and complex techniques are effective tools in predicting organizational outcomes. Accessible syntax and guides for beginners are also provided.