Improvement of natural image search engines results by emotional filtering

International audienceWith the Internet 2.0 era, managing user emotions is a problem that more and more actors are interested in.Historically, the first notions of emotion sharing were expressed and defined with emoticons. They allowedusers to show their emotional status to others in an impersonal and emotionless digital world. Now, in theInternet of social media, every day users share lots of content with each other on Facebook, Twitter, Google+and so on. Several new popular web sites like FlickR, Picassa, Pinterest, Instagram or DeviantArt are nowspecifically based on sharing image content as well as personal emotional status. This kind of information iseconomically very valuable as it can for instance help commercial companies sell more efficiently. In fact, withthis king of emotional information, business can made where companies will better target their customersneeds, and/or even sell them more products.Research has been and is still interested in the mining of emotional information from user data since then.In this paper, we focus on the impact of emotions from images that have been collected from search imageengines. More specifically our proposition is the creation of a filtering layer applied on the results of suchimage search engines. Our peculiarity relies in the fact that it is the first attempt from our knowledge to filterimage search engines results with an emotional filtering approach