Case study: Events, Social Media, and urban information modeling

My case study  mainly focused on three main events that happened during 2011, which were the Egyptian revolution, Japan’s Tsunami, and Occupy movement in New York. Those events could be like any events happened in the world, except that regular people started to publish and make news within the big headlines.Users of social media websites, mainly twitter, where the news publishers,reading the whole picture of the event and through them,where able to understand the social context of the events.

Besides, I was focusing on the news feeds, which are instant tweets coming from the users at that certain place of event. The collection of tweeps (people who tweet) in the certain geographical location starts a hotspot or a hub of information production. Without understanding where this information is coming from ,geographically, the information will not be complete and could be misleading.

This fluid of information coming from people through social media could be a valuable source in understanding human landscape, the social complex structures and relationships between people and how they interact with each other. It is far more vibrant and interactive than other information sources such as the census since it shows how people with similar opinions interact together and “geographically” presents the human terrain of ideas. Specialists in campaigns, marketing, advertising, and socio cultural analysts could benefit from such information.

Harvesting social media feeds is through three operations:

-Extracting Data from social media servers using API (Parsing, integrating) and storing this data in a resident data base.

-Analyze the data

Twitter content revealed emergence of socio-cultural hot sports ,and provides advanced warning of forth coming events, as was the case with Tahrir square reference in Arab spring events of spring 2011.It also offers a mechanism to obtain a rapid assessment of the impact area of natural disasters as demonstrates by data collected during Japan’s Tsunami .It provides unparalled situational awareness by supporting the monitoring of evolving events, as was the case with the Occupy Brooklyn bridge experiment.