ScatterBlogs offers solutions that allow analysts, decision-makers, and journalists to detect important events through social media like Twitter or Facebook and identify relevant content by making the data deluge manageable. And the best part: everything works in real-time. All results are updated dynamically with every written Tweet, posted Instagram picture, or uploaded YouTube video, world wide.
ScatterBlogs is a real-time enabled visual social media analytics solution. Harvest and evaluate Twitter, YouTube and Flickr data for precise and comprehensive situation awareness.
Modern situation assessment means big data intelligence. Put ScatterBlogs in your toolbox either as thin client or as a customized application that fits with your platform perfectly.
Cutting edge machine learning assigns location to non-geo-enabled posts, detects events based on spatiotemporal anomalies, and assists you in identifying relevant messages.
Traditional social media monitoring suffers from the low amount of information that can be assigned to a specific geographic location. ScatterBlogs includes a novel algorithm that automatically finds the location of messages with unknown origin based on its content and background information about the user.
Machine learning classifiers are a powerful tool to separate relevant information from signal noise. ScatterBlogs provides a mechanism to train, apply, and manage them interactively and visually. Analysts can create powerful classifiers from our recorded data repositories that accurately and precisely find all messages related to their topic of interest better than any list of keywords.
If many people talk about similar topics in a specific region and at the same time - that is what we call a spatiotemporal anomaly. It might be something harmless like a conference or a sporting event. But sometimes these anomalies are the result of a sudden earthquake, forest fire, or power outage. ScatterBlogs automatically detects these anomalies and visualizes them in a comprehensive fashion.