Historically, journalists have manually selected news. This process has been changing dramatically with the development of personalized news aggregators (PNAs), which rely on social recommender systems (SRSs) technology. PNAs provide content geared to the personal preferences of news consumers, and thus offer new business opportunities for news providers. However, little research exists on users’ intention to use PNAs or their willingness to pay (WTP) for such services. We developed PNA prototypes based on hybrid and social recommender systems and tested their performance in an online experiment. While the results showed little difference in users’ intention to use either system, content provided by SRSs was perceived as more accurate. Furthermore, the optimal price point for the social recommender system (€1.68) was 68% higher than the price point for the hybrid recommender system.