Abstract: An online system automatically selects one or more content items in a digital magazine for recommendation based on a common theme of the content items and similarities of the content items. In one aspect, content items are associated with different latent topics. A latent topic identifies a theme or a concept of related content items, where the theme is determined based on a probability of words appearing together in one or more content items sharing the identified theme. From a set of content items on a common latent topic with a subject content item, one or more content items may be automatically identified based on content proximity scores of the set of content items with respect to the subject content item. One or more content items having a content proximity score within a predetermined range with the subject content item are selected for recommendation to a user.