Towards attitudinal change in news recommender systems: A pilot study on climate change

Personalized recommender systems facilitate decision-making in various domains by presenting content closely aligned with users’ preferences. However, personalization can lead to unintended consequences. In news, selective information exposure and consumption might amplify polarization, as users are empowered to seek out information that is in line with their own attitudes and viewpoints. However, personalization in terms of algorithmic content and persuasive technology could also help to narrow the gap between polarized user attitudes and news consumption patterns.
This paper presents a pilot study on climate change news. We examined the relation between users’ level of environmental concern, their preferences for news articles, and news article content. We aimed to capture a news article’s viewpoint through sentiment analysis. Users (N = 180) were asked to read and evaluate 10 news articles from the Washington Post. We found a positive correlation between users’ level of environmental concern and whether they liked the article. In contrast, no significant correlation was found between sentiment and environmental concern. We argue why a different type of news article analysis than sentiment is needed. Finally, we present our research agenda on how persuasive technology might help to support more exploration of news article viewpoints in the future.