People you may ignore : users’ perceptions about social matching systems on social network sites

As the amount of information on the web grows exponentially every year, users rely more and more on recommender systems to find relevant content. On social network sites, recommender systems help users access not only relevant content, but also to connect to people of interest. Due to their central role in social network sites, people-to-people recommender systems have recently gained more attention among the academic community, especially in regards to reciprocity, privacy and their efficiency. This research aims to understand how people-to-people recommender systems may influence the establishment of new relationships outside and within social media. Therefore, eight social media users were interviewed with a semi-structured questionnaire about their experiences with recommender systems on different social media, such as Facebook, Twitter, Instagram and LinkedIn. All the interviewed users have been using social media for approximately 10 years. The interviews showed that the relevance of people-to-people recommender systems changes progressively, as users spend more time on social network sites. Considering the profile of the interviewed users and their long exposure to social media, most affirmed to ignore people-to-people recommender systems while browsing throughout social network sites. However, it was possible to conclude that the use of recommender systems in early stages had influenced how they perceive social network sites and how they relate to unknown users in virtual communities. As a result, this research presents an urgent need and suggestions to improve the design of people-to-people recommender systems, considering the different stages of use of social network sites. A special attention is recommended towards special user groups, such as children, and cultural differences