2020/03/06 by Seki, Kazuhiro, Ikuta, Yusuke
#Computation and Language (cs.CL) #Computers and Society (cs.CY) #FOS: Computer and information sciences #Social and Information Networks (cs.SI)
paper · doi:10.48550/arxiv.2003.02973
This paper describes our work on developing a new business sentiment index using daily newspaper articles. We adopt a recurrent neural network (RNN) with Gated Recurrent Units to predict the business sentiment of a given text. An RNN is initially trained on Economy Watchers Survey and then fine-tuned on news texts for domain adaptation. Also, a one-class support vector machine is applied to filter out texts deemed irrelevant to business sentiment. Moreover, we propose a simple approach to temporally analyzing how much and when any given factor influences the predicted business sentiment. The validity and utility of the proposed approaches are empirically demonstrated through a series of experiments on Nikkei Newspaper articles published from 2013 to 2018.