The project proposes a system that provides tools for internet users to find content online. In light of the massive and ever increasing amount of information available online, the need for more efficient tools to navigate and sort information is becoming more important.

The LOOP allows the user to use social information e.g. view count (i.e. how popular a video, article or link is) as a filter/tool to find interesting links. The user can also control who this social information is based on. It is possible to choose a part of the world such as China or Europe and the result of the search will be sorted based exclusively on the social information from that region. Another option is to base the search on one or more of the user’s contact groups. The user can easily find links e.g. music, videos or articles that are popular in a group that shares the user’s tastes and interests. Apart from choosing where the social information is coming from, the user also has several sorting options. These include traditional ones like view count, alphabetical and ratings as well as sorting according to a popularity forecast, buzz factor (how frequent the link is sent between people) and spreading rate.

The logic behind the LOOP system is inspired by social psychology theories. Social psychology is the study of how people’s thoughts, feelings, and behaviors are influenced by the actual or imagined presence of others (Allport, 1985). Social information, information about behavior on a group level, such as what content is popular online is gathered when we watch videos, listen to music and read articles on the web. Youtube is a good example of where social information helps the user assess the value and quality of a video before choosing to watch it. The view count and user’s ratings can help us determine if the quality of the video is good and if previous viewers have appreciated content of the video. There are also sites that offer the possibility to analyze a link to find out more about the social information gathered about it. Graphs tell us about the rise and fall of the popularity of the link and it is also possible to see from where in the world people have been viewing the link. This information is also used by marketers to predict the interests of a user by collecting taste information from many users (called collaborative filtering). The LOOP proposes that such social information can be used by the user herself to find content that is meaningful for her. This is also an attempt to democratize the evaluation of online content. Instead allowing an editor decide which is a main headline, the user’s actions, such as reading what is interesting to them, determine the “value” of the article. One can also argue that by simply giving the user access to this social information, which is normally controlled for commercial purposes, a more democratic state is achieved.

The project took its point of departure in a previous project dealing with weather forecasts. Central questions included what do we want to know and what information do we trust.