With the growing popularity of Twitter, numerous issues surround the usefulness of the technology for intelligence, defense, and security. For security, Twitter provides a real-time opportunity to determine unrest and discontent. For defense, twitter can be a source of open- source intelligence (INT) information related to areas of contested environments. However, the semantic content, location of tweets, and richness of the information requires big data analysis for understanding the use of the information for intelligence. In this paper, we describe some results in using twitter data to determine events, the semantic implications of the results from the data, as well as discuss pragmatic uses of twitter data for multi-INT data fusion. The results collected during the period of Egypt Arab spring conclude that (1) many tweets are clutter or noise in analysis, (2) location information does not always convey the accuracy of the information, and (3) the aggregate processing of the twitter data results in real-time trends of possible events that warrant more conventional information gathering.
['Aleksey Panasyuk', 'Erik Blasch', 'Sue Kase', 'Liz Bowman']
Extraction of Semantic Activities from Twitter Data.