A remarkable growth in quantity and popularity\ud of online social networks has been observed in recent years.\ud There is a good number of online social networks exists\ud which have over 100 million registered users. Many of these\ud popular social networks offer automated recommendations\ud to their users. This automated recommendations are\ud normally generated using collaborative filtering systems\ud based on the past ratings or opinions of the similar users.\ud Alternatively, trust among the users in the network also can\ud be used to find the neighbors while making\ud recommendations. To obtain the optimum result, there must\ud be a positive correlation exists between trust and interest\ud similarity. Though the positive relations between trust and\ud interest similarity are assumed and adopted by many\ud researchers; no survey work on real life people’s opinion to\ud support this hypothesis is found. In this paper, we have\ud reviewed the state-of-the-art research work on trust in\ud online social networks and have presented the result of the\ud survey on the relationship between trust and interest\ud similarity. Our result supports the assumed hypothesis of\ud positive relationship between the trust and interest\ud similarity of the users
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