Exploring Sentiment Polarity of P2P Guests Through Online User Reviews: A Multimodal Fuzzy Approach
提出一种多模态模糊模型，利用VADER、词嵌入等技术分析P2P住宿在线评论中的情感倾向，并考察新冠疫情对房客情感的影响，为行业提供策略参考。
The popularity of peer-to-peer (P2P) housing services has increased the demand for understanding guests' emotional experiences and sentiments towards these services. This study aims to fill this gap by analyzing guests' emotional tendencies expressed in online reviews of P2P housing services. Our approach proposes a novel multimodal fuzzy model that addresses the limitations of previous studies, such as the inability to capture the complexity and subjectivity of emotions accurately. The model leverages advanced text processing technologies, including the valance-aware dictionary and sentiment reasoner (VADER), count-vectorization, and word embedding, to provide a more nuanced and objective analysis of guests' sentiment and emotional valence. Additionally, this study examines the impact of the COVID-19 pandemic on guests' emotional tendencies and P2P innovative strategies. The results of this study have the potential to enhance effective strategies for the P2P industry and advance the field of sentiment analysis in the P2P domain.