1. A system for early detection of civil unrest events, the system comprising: one or more processors and a non-transitory computer-readable medium having executable instructions encoded thereon such that when executed, the one or more processors perform operations of: receiving a set of textual social media data having corresponding user identifications as input; filtering the set of textual social media data with a keyword filter, resulting in a first set of data comprising keywords of interest; filtering the first set of data with a future date filter, resulting in a second set of data comprising future dates; filtering the second set of data based on relevance to a civil unrest event with a text classifier module, resulting in a third set of data that is classified based on relevance to the civil unrest event; filtering the third set of data based on a location of interest, resulting in a fourth set of data having user identifications in the location of interest; assigning a location to the civil unrest event; and outputting a forecast of the civil unrest event.
1. A system for early detection of civil unrest events, the system comprising: one or more processors and a non-transitory computer-readable medium having executable instructions encoded thereon such that when executed, the one or more processors perform operations of: receiving a set of textual social media data having corresponding user identifications as input; filtering the set of textual social media data with a keyword filter, resulting in a first set of data comprising keywords of interest; filtering the first set of data with a future date filter, resulting in a second set of data comprising future dates; filtering the second set of data based on relevance to a civil unrest event with a text classifier module, resulting in a third set of data that is classified based on relevance to the civil unrest event; filtering the third set of data based on a location of interest, resulting in a fourth set of data having user identifications in the location of interest; assigning a location to the civil unrest event; and outputting a forecast of the civil unrest event. 21. The system as set forth in claim 1 , wherein the text classifier module further comprises a user type identification classifier to determine whether a user identification is related to an individual or an organization, and wherein the one or more processors further perform an operation of increasing the probability of the civil unrest event occurring if the user identification is related to an organization.