: The development of a self-administered conversation analysis based training programme for cochlear implant users.

Training software to facilitate participation in conversations where overlapping talk is common was to be developed with the involvement of Cochlear implant (CI) users. Examples of common types of overlap were extracted from a recorded corpus of 3.5 hours of British English conversation.

Beyond opinion classification: Extracting facts, opinions and experiences from health forums.

Introduction: Surveys indicate that patients, particularly those suffering from chronic conditions, strongly benefit from the information found in social networks and online forums. One challenge in accessing online health information is to differentiate between factual and more subjective information. In this work, we evaluate the feasibility of exploiting lexical, syntactic, semantic, network-based and emotional properties of texts to automatically classify patient-generated contents into three types: "experiences", "facts" and "opinions", using machine learning algorithms.