This tutorial will introduce the concepts of social media and sentiment analysis from unstructured text. It will first introduce the concept of social media analysis, showing how this form of noisy text requires different solutions from traditional text analysis, with practical examples and exercises showing how this can be achieved. This leads into the more specialised task of sentiment analysis: the problem of extracting opinions automatically from text. It will cover both rule-based and machine learning techniques, provide some information on the key underlying NLP and text analysis processes required, and look in detail at some of the major problems and solutions, such as detection of sarcasm, use of informal language, spam opinion detection, trustworthiness of opinion holders, and so on. 

Tutorial by Diana Maynard.