Automated social-media content analysis is becoming the key ingredient to help us to understand web trends, user behaviour and to help predict advertising campaigns. Performing this analysis in real-time is therefore extremely important for big brands to timely plan their marketing strategies and to make effective decisions. The computer vision community is investing heavily in the analysis of subjective attributes with regards visual content. Memorability, popularity, virality and emotional content are just a few examples of the attributes that Artificial Intelligence (AI) algorithms can automatically understand from images and videos.
In this project, candidate students will help to create a web platform to analyse social feeds from Facebook, Twitter, Instagram, etc., in real-time and then to predict subjective attributes. We will guide you through the usage of Deep Learning techniques, social feed crawling (e.g. https://www.norconex.com/how-to-crawl-facebook/) and advanced data analytics. This web platform will then go live along with a comprehensive API and it will provide users with unique tools to help predicted social-media trends.
Required knowledge and skills
- FBK Internship opportunities are open to students (pre-lauream internship) and post-graduates (within 12 months from graduation - post lauream internship) only
- According to the Italian law, post-graduate internships can last up to 6 months and must be activated within 12 months from the graduation.
- Apply Online. Please make sure to attach your CV and short cover letter as one single file.