This project aims to address the challenge of opinion mining of multimedia content from the web. This comprises a large-scale multi-modal analysis of social media streams and their underlying network dynamics considering different media channels such as Twitter, Flickr, YouTube, Google, and Wikipedia. The main contribution of MOM is four-fold:
- Social media data is analyzed utilizing information from structured data sources to detect and track trending topics.
- Large amounts of multimedia content are analyzed with respect to its sentiment and opinion. This follows a holistic approach i.e. the analysis of a rich set of different modalities such as textual, visual, and tempo-visual content.
- This information is further enriched by network analysis to grasp structural diffusion as well as global and local impact of information in social networks.
- The possibility of forecasting the progression of identified opinion topics into the near future is investigated.
