TY - JOUR AU - Enevoldsen, Kenneth C. AU - Hansen, Lasse PY - 2017/07/07 Y2 - 2024/03/28 TI - Analysing Political Biases in Danish Newspapers Using Sentiment Analysis JF - Journal of Language Works - Sprogvidenskabeligt Studentertidsskrift JA - LWorks VL - 2 IS - 2 SE - Articles DO - UR - https://tidsskrift.dk/lwo/article/view/96014 SP - 87-98 AB - Traditionally, the evaluation of political biases in Danish newspapers has been carried out through<br />highly subjective methods. The conventional approach has been surveys asking samples of the<br />population to place various newspapers on the political spectrum, coupled with analysing voting<br />habits of the newspapers’ readers (Hjarvard, 2007). This paper seeks to examine whether it is<br />possible to use sentiment analysis to objectively assess political biases in Danish newspapers. By<br />using the sentiment dictionary AFINN (Nielsen et al., 2011), the mean sentiment scores for 360<br />articles was calculated. The articles were published in the Danish newspapers Berlingske and<br />Information and were all regarding the political parties Alternativet and Liberal Alliance. A<br />significant interaction effect between the parties and newspapers was discovered. This effect was<br />mainly driven by Information’s coverage of the two parties. Moreover, Berlingske was found to<br />publish a disproportionately greater number of articles concerning Liberal Alliance than<br />Alternativet. Based on these findings, an integration of sentiment analysis into the evaluation of<br />biases in news outlets is proposed. Furthermore, future studies are suggested to construct datasets<br />for evaluation of AFINN on news and to utilize web-mining methods to gather greater amounts of<br />data in order to analyse more parties and newspapers. ER -