A Study on the Diversity and Political Bias of Personalized News: The Case of Korea’s Internet News Portals

As the use of digital news services increases, service providers recommend news articles based on readers’ interests and preferences. In this study, we analyzed the differences in news diversity, the number of political news articles, and the political bias of personalized news compared to non-personalized news, focusing on Naver News and Kakao News, Korea’s representative news aggregators. Additionally, we investigated whether readers’ political orientation affects the political bias of personalized news. Through a survey company, we recruited 299 adults aged 20 to 59 who had used Internet news portals for at least 10 min daily over the past month. An online survey was conducted to measure demographic variables, news usage, political orientation, and an online quasi-experiment was carried out to examine the news articles provided to them through Internet news portals in both logged-in and logged-out states. The results indicated that personalized news has lower content diversity, higher source diversity, and provides fewer political news articles compared to non-personalized news. In the case of Naver News, personalized news was more neutral in terms of coverage and statement bias than non-personalized news. Furthermore, news readers’ political orientation did not have a statistically significant effect on the coverage and statement bias of personalized news. Before the introduction of personalized news, Internet news portals in South Korea were suspected of being politically biased. The results of this study suggested that personalized algorithms did not provide more politically biased news articles than conventional news delivery systems and did not cause filter bubbles.