Use Case: Monitoring Social Media to Assess The Impact of The Eruption of Mount Agung in Bali, Indonesia
Staying informed about emerging and rapidly developing critical issues and events is important for many professions. PR- executives, information managers and decision makers of governmental institutions, commercial associations, humanitarian organizations, first responders or political parties all need to stay on top of events as they unfold in order to provide rapid assessment and advice concerning actions to be taken. However, especially the great variety and different kinds of social media platforms create vast and almost unmanageable amounts of information in a continuous manner. The challenge for information professionals then comes in coping with this data deluge and in transforming it into something that is meaningful – into actionable information. Manual solutions like monitoring and analysis of traditional and social media in a 24 x 7 mode, browsing websites, or listening to hundreds of YouTube channels are possible, but aren’t efficient and certainly do not scale. The SAIL LABS Media Mining System is a tool geared towards precisely this task: data from traditional and social media are collected and processed automatically, enriched and analyzed and subsequently visualized in the Media Mining Client (MMC). Under the full control of the organization, data is gathered from trusted and relevant sources. Using a set of filtering and visualization capabilities, the important documents can be retrieved quickly and data visualized for further analysis. The Social Media Extension (SME) provides an advanced interface to explore data from a variety of social media sources (currently Twitter, Vkontakte, Facebook and YouTube). A central dashboard presents an overview of social media documents, actors and links. Detailed panels allow to explore different aspects of the data in more detail. This white-paper focuses on the SME, its use and benefits. The information presented will enable you to effectively use this feature within the MM-System thus unleashing the full social media analytics potential.