# S-APIR: News-based Business Sentiment Index

arXiv: https://arxiv.org/abs/2003.02973 · HTML: https://mlsanity.com/paper/2003.02973/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Mar 2020.

## Built on by (most cited first, 1 of 1)

- [News-based Business Sentiment and its Properties as an Economic Index](https://mlsanity.com/paper/2110.10340/) (2021)

## Abstract (arXiv)

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.