Detecting future social unrest in unprocessed Twitter data: “Emerging phenomena and big data”

Ryan Compton · Craig Lee · Tsai-Ching Lu · Lalindra De Silva · Michael Walton Macy

45 citations0/0 files storedIEEE International Conference on Intelligence and Security Informatics (ISI)

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Computational and Text Analysis Methods Public Relations and Crisis Communication Information Retrieval and Data Mining

Abstract

We have implemented a social media data mining system capable of forecasting events related to Latin American social unrest. Our method directly extracts a small number of tweets from publicly-available data on twitter.com, condenses similar tweets into coherent forecasts, and assembles a detailed and easily-interpretable audit trail which allows end users to quickly collect information about an upcoming event. Our system functions by continually applying multiple textual and geographic filters to a large volume of data streaming from twitter.com via the public API as well as a commercial data feed. To be specific, we search the entirety of twitter.com for a few carefully chosen keywords, search within those tweets for mentions of future dates, filter again using various logistic regression classifiers, and finally assign a location to an event by geocoding retweeters. Geocoding is done using our previously-developed in-house geocoding service which, at the time of this writing, can infer the home location for over 62M twitter.com users [1]. Additionally, we identify demographics likely interested in an upcoming event by searching retweeter's recent posts for demographic-specific keywords.

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2018Mining location from social media: A systematic review 2016The Geography and Importance of Localness in Geotagged Social Media 2016On predicting social unrest using social media 2017Forecasting Civil Unrest Using Social Media and Protest Participation Theory 2014Using publicly visible social media to build detailed forecasts of civil unrest 2014Civil Unrest Prediction: A Tumblr-Based Exploration 2015Event Prediction With Learning Algorithms—A Study of Events Surrounding the Egyptian Revolution of 2011 on the Basis of Micro Blog Data 2017Multiview Deep Learning for Predicting Twitter Users' Location

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