Abstract
This paper proposed a new approach for the extraction of tags from users' comments made about videos. In fact, videos on the social media, like Facebook and YouTube, are usually accompanied by comments where users may give opinions about things evoked in the video. The main challenge is how to extract relevant tags from them. To the best of the authors' knowledge, this is the first research work to present an approach to extract tags from comments posted about videos on the social media. We do not pretend that comments can be a perfect solution for tagging videos since we rather tried to investigate the reliability of comments to tag videos and we studied how they can serve as a source of tags. The proposed approach is based on filtering the comments to retain only the words that could be possible tags. We relied on the self-organizing map clustering considering that tags of a given video are semantically and contextually close. We tested our approach on the Google YouTube 8M dataset, and the achieved results show that we can rely on comments to extract tags. They could be also used to enrich and refine the existing uploaders' tags as a second area of application. This can mitigate the bias effect of the uploader's tags which are generally subjective.