Interpretable fake review detection based on multimodal information and human–computer collaboration

Key Points

• The implementation of multimodal information improves the detection of fake reviews, with a notable enhancement in accuracy.
• Analysis reveals that human-computer collaboration significantly decreases false positive rates in identifying fraudulent content.
• The approach uses advanced machine learning algorithms which streamline the process of filtering genuine reviews from fake ones.
• This technique is vital for online platforms, highlighting the need for continual improvement to safeguard user trust.