Collecting and Managing Real-life Event Information from Social Media

With the popularity of social media platforms such as Facebook and Twitter, there has been voluminous growth in the digital footprints of real-life events on the Internet. The user-generated colloquial and concise textual content related to different types of real-life events, available in these websites, acts as an extremely useful source for researchers and organizations for extracting valuable and insightful information. There has been significant improvement in natural language processing techniques for mining formal and long textual content commonly found in newspapers. It is still a challenging task to mine textual information from the social media channels producing terse, informal and noisy text with an unusual grammatical structure. For a real-life event of interest it is necessary to detect and store informative event-specific signals from the noisy social media channels that allows to distinctly identify the event among all others, and characterizes it for extracting actionable insights. This book explores such methods and techniques along with presenting some novel approaches.