Mining Reviews by BERT in Tweets on Actors and Characters of TV Drama

Abstract

This paper proposes how to mine concerns and reviews that are relevant to TV dramas from the results of collecting tweets on those TV dramas. The task studied in this paper is to identify tweets which include reviews and impressions of actors and characters of those TV dramas. In order to formalize this task, we apply the machine comprehension framework of BERT, where each tweet is considered as the context of machine comprehension and the name of an actor or a character is given to this tweet as a question and an adjective representing its reviews or impressions is returned as the answer to the question. Experimental evaluation results show that the proposed approach achieved over 70% recall and precision.