Sentiment Analysis of Economic Text: A Lexicon-Based Approach

TL;DR

This paper introduces an Economic Lexicon tailored for sentiment analysis in economic texts, demonstrating its superior coverage and accuracy over existing lexicons through various economic applications.

Contribution

The paper presents a novel domain-specific lexicon with human-annotated sentiment scores, improving sentiment analysis accuracy in economic contexts.

Findings

EL outperforms existing lexicons in economic sentiment tasks

Wider domain coverage improves sentiment categorization

Application examples demonstrate practical utility

Abstract

We propose an Economic Lexicon (EL) specifically designed for textual applications in economics. We construct the dictionary with two important characteristics: 1) to have a wide coverage of terms used in documents discussing economic concepts, and 2) to provide a human-annotated sentiment score in the range [-1,1]. We illustrate the use of the EL in the context of a simple sentiment measure and consider several applications in economics. The comparison to other lexicons shows that the EL is superior due to its wider coverage of domain relevant terms and its more accurate categorization of the word sentiment.