Towards a selfie social network with automatically generated sentiment-bearing hashtags

Web 2.0 has witnessed increased focus on more user generated content and eventually on data analyzed and queried in meaningful ways. Selfies, a new form of user-generated content, have become an important part of the visual communication in social media. A large portion of images posted on some social networks are selfies. Behind each of these selfies lie the sentiments of the person in the photo posted. The authors of this paper believe that adding quantified sentiment indicators to these selfies can be a valuable addition to not only the social network users but also to the many networks already in existence. Motivated by the idea, the authors propose an addition to social networks that automatically captures the sentiments expressed in selfies as they are being posted. The captured sentiments are then presented along with the selfies' on the users' timeline. In this research, the authors propose Momented, a selfie social network. Momented works by tracking the sentiments expressed in the selfies posted on the Momented social network. Based on the emotions tracked from a particular selfie, the system automatically generates sentiment bearing hashtags. Tthe selfie along with the automatically generated hash tags are posted on the user's dashboard timeline.