Maps help extract meaning from the large volume of social media messaging, providing context and a means for connections. Increasingly, we’re seeing the mapping of Twitter messages and more sophisticated tools to spatially analyze this data in order to make more sense of it. Sense2Place is a compelling new research project from the Penn State GeoVISTA Center that filters tweets on place-time attributes, analyzing changing issues and perspectives over time.
As we’re witnessing this week, the ability to map this data is immensely helpful in a crisis situation, but what is often lacking in the interface is a sense of time or an understanding of how the situation has evolved. We’re still seeing the myriad map interfaces that have been created for the earthquake in Japan with videos of waves as the most prominent feature, although that stage of the disaster was days ago, and what’s most important is connecting loved ones and beginning the cleanup process.
What’s needed is a means to temporally filter out old messages, and memes, and provide an up-to-date and timely exchange of place-based information. The ability of Sense2Place to filter the time dimension makes this approach a compelling option to make more sense of the chaos of this crisis.
