Social networking systems are online services, computers, platforms, or websites, or combinations thereof, which facilitate the building of social networks or social relations among people. For example, users of a social networking system can share interests, arrange activities, or even make real-life connections. An Internet-based social networking system can use representations (profiles) of the users, social links of the users, and various services to help the user to interact with and extend their social networks.
Using social networking systems, a person can grow his/her social network by discovering people who have similar interests or experiences. However, it can take a substantial amount of time and effort to identify such people. Finding unfamiliar people who share one's interests is difficult. It is not uncommon that two strangers spend a long and awkward conversation and interaction (online or face-to-face) to discover their common interests or experience.
Even with current social networking systems designed to aid the process of connecting people, the process is still primarily cumbersome and static. For example, a typical social networking website requires users to provide biographical information by filling out profile forms. A user can disclose his or her interests by providing personal information such as professional interests, career information, interests in media, political opinions and religious beliefs. A matching algorithm then uses the profile and interest data provided by the user to match other users who are determined to be like-minded by the algorithm. However, the success rate of the matching algorithm depends on the quality of the data entered by the users. For various reasons, a user may provide incomplete, inaccurate, or even misleading data that does not well represent the actual interests of the user. Further, users rarely bother to update their profile and interest data, while their interests can constantly change over time. The profile and interest data only reflects a static and potentially inaccurate image of a user at the time when the user provides the profile and interest data. Therefore, a matching algorithm such as discussed above can have a low success rate.