Using Machine Learning for Analyzing Sentiment Orientations Toward Eight Countries

Shesen Guo,Ganzhou Zhang

doi:10.1177/2158244020951268

Abstract

By using machine learning technique, this article presents sentiment and concept analyses on 48,043 articles published in The Economist from 1991 through 2016. The Economist is one of the world’s most influential political and economic magazines. The article analyzes and compares the magazine’s sentiment orientations toward the Group of Seven’s ingroup member countries (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) and its outgroup member country China. The sentiment analyses are performed on and compared between different periods of Clinton’s, Bush’s, and Obama’s administrations in the United States; Major’s, Blair’s, Brown’s, and Cameron’s cabinets in the United Kingdom; and Kohl’s, Schröder’s, and Merkel’s in Germany. The relationship between China hosting the Olympic Games or its growing economic power and the magazine’s sentiment orientations toward the country is examined. The concept analysis on the articles with extreme positivity or negativity shows that there is no difference between the ingroup and outgroup members in the topics covered in The Economist.

Highlights

Sentiment, like human attitude or opinion, exists in discourse or texts (B. Liu, 2015; B. Liu et al, 2005). Van Dijk (2013) states that it is by text that people acquire, spread, and reproduce ideology, and texts can typically represent “our” positive properties and “their” negative properties
Taking into account the speed that our computer connected to the sentiment API, simplicity of interface language for implementing API, cost, and the classification performance F1 score, we used Watson NLU to perform sentiment analysis (SA) on all the downloaded The Economist (TE) data
Given the amount of sample data and the long time span in this investigation, the above negative values may represent a general picture of TE’s sentiment orientations in 1991 to 2016. Considering that it is largely a magazine reporting politics and economy of different countries, we propose that at least from the point of view of language selection and use in TE from 1991 through 2016, TE’s overall attitudes toward countries, events, the world, leaders, and masses are slightly negative or near politically or ideologically neutral

Summary

Introduction

Like human attitude or opinion, exists in discourse or texts (B. Liu, 2015; B. Liu et al, 2005). Van Dijk (2013) states that it is by text that people acquire, spread, and reproduce ideology, and texts can typically represent “our” positive properties and “their” negative properties. What is TE’s overall sentiment score based on SA on the articles about the eight countries (the G7’s member countries and China) over a long period of time?

Results

Conclusion