Abstract:
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The rising popularity of social media has resulted in organizations of all types, including not-for-profits, attempting to use the social streams to inform managerial decisions. However, using data from popular social media platforms can be challenging due to the varied and dynamic nature of the data, including variance in popularity and topic both time and space. For instance, a communication posted to a social media platform can vary in its physical location or origin, time of arrival, and content. In this work, we discuss the integration of two geolocated and time varying datasets to study the relationship between Twitter usage around crisis events, like hurricanes, and donation patterns to a major nonprofit organization. By combining time-series forecasting, and spatiotemporal analysis, we develop insights into how a nonprofit organization could utilize Twitter usage patterns to improve the timing and targeting of marketing communications.
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