Query-based opinion summarization for legal blog entries

摘要

We present the first report of automatic sentiment summarization in the legal domain. This work is based on processing a set of legal questions with a system consisting of a semi-automatic Web blog search module and FastSum, a fully automatic extractive multi-document sentiment summarization system. We provide quantitative evaluation results of the summaries using legal expert reviewers. We report baseline evaluation results for query-based sentiment summarization for legal blogs: on a five-point scale, average responsiveness and linguistic quality are slightly higher than 2 (with human inter-rater agreement at k = 0.75). To the best of our knowledge, this is the first evaluation of sentiment summarization in the legal blogosphere.