An Opinion Summarization-Evaluation System Based on Pre-trained Models

As social media appeal more frequently used, the task of extracting the mainstream opinions of the discussions arising from the media, i. e. opinion summarization, has drawn considerable attention. This paper proposes an opinion summarization-evaluation system containing a pipeline and an evaluation module for the task. In our algorithm, the state-of-the-art pre-trained model BERT is fine-tuned for the subjectivity analysis, and the advanced pre-trained models are combined with traditional data mining algorithms to gain the mainstreams. For evaluation, a set of hierarchical metrics is also stated. Experiment result shows that our algorithm produces concise and major opinions. An ablation study is also conducted to prove that each part of the pipeline takes effect significantly.