Analysing Political Biases in Danish Newspapers Using Sentiment Analysis

Abstract

Traditionally, the evaluation of political biases in Danish newspapers has been carried out throughhighly subjective methods. The conventional approach has been surveys asking samples of thepopulation to place various newspapers on the political spectrum, coupled with analysing votinghabits of the newspapers’ readers (Hjarvard, 2007). This paper seeks to examine whether it ispossible to use sentiment analysis to objectively assess political biases in Danish newspapers. Byusing the sentiment dictionary AFINN (Nielsen et al., 2011), the mean sentiment scores for 360articles was calculated. The articles were published in the Danish newspapers Berlingske andInformation and were all regarding the political parties Alternativet and Liberal Alliance. Asignificant interaction effect between the parties and newspapers was discovered. This effect wasmainly driven by Information’s coverage of the two parties. Moreover, Berlingske was found topublish a disproportionately greater number of articles concerning Liberal Alliance thanAlternativet. Based on these findings, an integration of sentiment analysis into the evaluation ofbiases in news outlets is proposed. Furthermore, future studies are suggested to construct datasetsfor evaluation of AFINN on news and to utilize web-mining methods to gather greater amounts ofdata in order to analyse more parties and newspapers