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Recommender systems have been strongly researched within the last decade. With the arising and popularization of digital social networks a new field has been opened for social recommendations. Considering the network topology, users interactions, or estimating trust between users are some of the new strategies that recommender systems can take into account in order to adapt their techniques to these new scenarios. We introduce MarkovTrust, a way to infer trust from Twitter interactions and todoi:10.1109/asonam.2012.200 dblp:conf/asunam/LumbrerasG12 fatcat:5pia2hxbcjemhognvvwiqbso2m