Exploring the challenges of remote work on Twitter users' sentiments: From digital technology development to a post-pandemic era
通过分析推特用户生成内容，运用情感分析和主题建模识别出远程工作的11个主题（包括虚拟健康、隐私担忧、工作生活平衡等），并总结出6个机会和5个挑战，为企业和管理者提供参考。
The boost in the use and development of technology, spurred by COVID-19 pandemic and its consequences, has sped up the adoption of new technologies and digital platforms in companies. Specifically, companies have been forced to change their organizational and work structures. In this context, the present study aims to identify the main opportunities and challenges for remote work through the use of digital technologies and platforms based on the analysis of user-generated content (UGC) in Twitter. Using computer-aided text analysis (CATA) and natural language processing (NLP), in this study, we conduct a sentiment analysis developed with Textblob, which works with machine learning. We then apply a mathematical algorithm for topic modeling known as Latent Dirichlet allocation (LDA) model. Based on the results obtained from these data-mining techniques, we identify 11 topics, of which 3 are negative (Virtual Health, Privacy Concerns and Stress), 4 positive (Work-life balance, Less stress, Future and Engagement), and 3 neutral (New Technologies, Sustainability, and Technology Issues). In addition, we also identify and discussed 6 opportunities and 5 challenges in relation to the use and adoption of digital technologies and platforms for teleworking. Finally, theoretical and practical implications of the study are presented for companies that develop strategies based on teleworking and the adoption of new technologies in which stress management is configured as one of the most relevant indicators for further research on remote work. From the applied perspective, executives and policymakers can use the results of the present study to re-evaluate the benefits of remote work for employees.