There are many possible applications for this; for example, analyzing Twitter messages in Baltimore and comparing those with events on the ground. Are those types of messages "archived" somewhere? Has anyone used social media in this manner?
Hi Jan!
This is a very interesting topic. Maybe you will be interested in these materials . These articles focus on a slightly different formulation of the question , but may be able to be helpful to identify the mythologizing of certain historical events.
http://iopscience.iop.org/0295-5075/99/2/28002/pdf/0295-5075_99_2_28002.pdf
http://arxiv.org/abs/1306.2537
Hi, if this is associated to a brand then you can certainly look for the brand community sites within Facebook. A wealth of historical data shall be available there. Hope it helps.
Hi Jan,
We spent about 2 years to build an intelligent platform to analyze social media and the rest of the web to detect anomalies and the trends in any given region. We call it "a bird's eye view" model. The platform released to public 1 month ago. You can learn more about the platform here: www.tilofy.com and I would be more than happy to give you free access to play with it and love to hear your feedback. Basically, our smart algorithms using machine learning and NLP to extract context from the offline world like a group of conversations from twitter or Instagram and analyze "whats happening in that given region in real-time". We have historical data for almost 1.5 years + real-time feed and our last phase is predictive model which is in progress. For example, if there is a marathon in LA today, Tilofy draws a heat map for you in real-time to see how the event evolve in the region and expand around the location. Basically, you can monitor the marathon from start to end in real-time and have access to all conversations, age, gender and race breakdown, sentiment, top influencers, pictures, videos, text, event start, pick time and end, tag cloud and taxonomy which determine other people interests about the same subject. All this information generating with the algorithms and is fully automated. I have a feeling that you might find the platform very interesting for your research.
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