Social media recommendation based on people and tags
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
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Nowadays, a lot of people post various contents to the video sharing services. To find good contents, it is necessary something high-quality content search and contents classification method, and the method should understand user's taste and user's context. In this paper, we propose a ranking method based on viewer's comments, especially amount of "funny" feelings comments given by consumer. We also evaluate the questionnaire for our method. Our proposed method is assumed to be applicable to all types of content, if it given a lot of comments from people.