Recommendation and Collaborative Filtering

Recommendation tools are now a common component in many online sites which involve a user choosing to view or purchase items based on personal preferences. For example, books, movies, music, hotels, restaurants, etc.

Collaborative Filtering techniques are one approach to recommendation. These techniques use the previous preferences of users to recommend new items to a user.

Despite the prevalence of recommendation techniques, the area still remains a fruitful research one, from the perspectives of data available, approaches and techniques used and the analysis of the usefulness and novelty of recommendations, and many others.

Social Media Analysis and Tools

The advent of Social Media sites offers many new sources of data to analyse and use in novel ways. We have now available a vast amount of information about people, brands and corporations – what they say and what is said about them, who they connect to and who connects with them, how they respond to events and become authorities on events. Wars, sport, elections, floods, famines can all be viewed through the lenses of social media activity.

In particular, sentiment analysis techniques can be applied to analyse the influence and reach of brands and people. This analysis will most likely involve the following steps: gathering data from a social media forum (e.g. Twitter), categorising and clustering the data based on features and on sentiment; and identifying trends in the data.