Polarity Calibration for Opinion Summarization

Understand

Opinion summarization is automatically generating summaries from a variety of subjective information, such as product reviews or political opinions.

• The challenge of opinions summarization lies in presenting divergent or even conflicting opinions.
• We conduct an analysis of previous summarization models, which reveals their inclination to amplify the polarity bias, emphasizing the majority opinions while ignoring the minority opinions.
• To address this issue and make the summarizer express both sides of opinions, we introduce the concept of polarity calibration, which aims to align the polarity of output summary with that of input text.