Год выпуска: 2012 Автор: Vasileios Lampos Издательство: LAP Lambert Academic Publishing Страниц: 220 ISBN: 9783659168642
Описание
A vast amount of textual web streams is influenced by events or phenomena emerging in the real world. The Social Web forms an excellent modern paradigm, where unstructured user generated content is published on a regular basis and in most occasions is freely distributed. The present book deals with the problem of inferring information — or patterns in general — about events emerging in real life based on the contents of this textual stream. We show that it is possible to extract valuable information about social phenomena, such as an epidemic or even rainfall rates, by automatic analysis of the content published in Social Media, and in particular Twitter, using Statistical Machine Learning methods. By examining further this rich data set, we also propose methods for extracting various types of mood signals revealing how affective norms evolve during the day and how significant events emerging in the real world are influencing them. Lastly, we present some preliminary findings showing...
