Abstract: Technologies for determining, displaying, and leveraging reasons to buy for categories of items. Aspects (reasons to buy) may be predetermined for categories of items from a corpus of item information. For each item in a category, community-sourced content (e.g., customer reviews) may be identified for (aligned to) each aspect, and relevant comments may be extracted from the content. The comments may be analyzed, for example according to sentiment, to provide scoring and summary statistics for the aspects. Items may be ranked according to the summary statistics. The aspects for an item may be displayed, with extracted comments and/or summary statistics provided for each aspect. Items in a category or across categories may be compared according to the aspects. Aspects may be used in searches for items within categories to filter the items according to one or more of the aspects.

Abstract: A device, system, and method determine, for each of a first group of content item sources of a social networking system, an output quality metric based on activity data accessed from an electronic data storage related to content items previously output by a respective content item source. Each of the content item sources are configured to output a ranked list of content items stored in the electronic data storage according to a ranking schema different for each of the content item sources. An integrated ranked list is generated based on the ranked lists of content items from each of the content item sources and the output quality metric of the respective content item sources. A content item stream is generated based on the integrated ranked list and ranked lists from each of a second group of content item sources different from the first group of content item sources.