Social Media Mining @ IPLAB

The terms Social Media Mining or Social Media Analysis refer to the study and development of techniques able to extract patterns and trends from multimodal data extracted from social platforms. This involves the exploitation of techniques for data crawling, representation, cleaning and analysis. As well as the development of Machine Learning systems able to detect contents that capture the attention of a large amount of users (Popularity), or infer opinion toward topics (Sentiment Analsis).

The diffusion of social networks plays a crucial role in collecting information about people opinion, trends and behaviour. The proliferation of mobile devices and the diffusion of social media, have changed the communication paradigm of people that share multimedia data, including text, video and images. From such user contributed data, its possible to study the interrelationship between users, and to model and predict user behaviour (e.g., preferences, search intent, purchase behaviour). Advanced techniques for translating large datasets built from crowdsourced data into clear actionable insights that create value for business and society can be developed. This research field focuses on novel models and systems able to take full advantage of the huge amount of the publicly available data generated by users every day.

The aim of this page is to present research done by the Image Processing LABoratory(IPLAB) in the scope of Social Media Mining.