PhD in "Using Social Network Analysis to Support User Model Construction"
This research will be focused on investigating techniques and technologies to support the construction of a model of a user based upon that user’s social web interactions, social networks and user-generated content.
The emergence of a new generation of social platforms has transformed user interaction and content production on the WWW. Blogs, wikis, photo sharing and social networking, to name but a few of these platforms, have opened up the WWW and allow any user to become a publisher of content. Social networking has become a massively popular means of communication and interaction online. With sites such as Facebook, Twitter, YouTube, Google, Flickr, LinkedIn and WordPress there are over a billion socially active people online today, and that number continues to grow at an astounding rate. This change in emphasis and utilisation of the WWW has come to be known as Web 2.0 and there is no longer any denying that this social Web is the new Web.
User modelling is a process by which a cognitive model is constructed which represents a human user. This model can include a variety of information about an individual such as their skills, knowledge, preferences, beliefs, needs etc. Web applications can use these user models to deliver more tailored and personalised experiences to each individual. The more knowledge about a user which can be modelled, the more effective such experiences can be, yet users do not like to be confronted with intrusive or irrelevant questions. However, the content available via many social web applications is potentially valuable in modelling users without the need to elicit this information directly from the user.
The goal of this research will be to investigate and develop innovative techniques and technologies to support the profiling of user activity and knowledge and the establishment of user preference. This will involve the linguistic analysis of users and their social network. The research will also investigate the acquisition of latent knowledge through multi-network analysis (Twitter, Facebook etc.). The PhD candidate will conduct cutting edge research in areas such as Natural Language Processing, Machine Learning and Social Network Analysis.