Abstract Details
Activity Number:
|
180
|
Type:
|
Contributed
|
Date/Time:
|
Monday, August 4, 2014 : 10:30 AM to 12:20 PM
|
Sponsor:
|
Section on Statistics in Marketing
|
Abstract #312621
|
View Presentation
|
Title:
|
Improving Donor Campaigns Around Crises with Twitter-Analytics
|
Author(s):
|
Chen Wang*+ and Shawn Mankad and William Rand
|
Companies:
|
Robert H. Smith School of Business and University of Maryland and Robert H. Smith School of Business
|
Keywords:
|
spatiotemporal ;
clustering ;
Twitter ;
visualization
|
Abstract:
|
Because of the rising popularity of social media, organizations of all types, including not-for-profits, monitor the associated data streams for improved prediction and assessment of market conditions. However, the size and dynamics of the data from popular social media platforms lead to challenging analysis environments, where observations and features vary in 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 geo-located and time varying datasets that are used to study the relationship between Twitter usage around crisis events, like hurricanes, and donation patterns to a major nonprofit organization. By combining visualization techniques, time-series forecasting, and clustering algorithms, we develop insights into how a nonprofit organization could utilize Twitter usage patterns to improve targeting of likely donors.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2014 program
|
2014 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Professional Development program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.