The Pulse of Public Opinion : Using Twitter Data to Analyze Public Perception of Reform in El Salvador

This study uses Twitter data to provide a more nuanced understanding of the public reaction to the 2011 reform to the propane gas subsidy in El Salvador. By soliciting a small sample of manually tagged tweets, the study identifies the subject matte...

Full description

Bibliographic Details
Main Authors: Seabold, Skipper, Rutherford, Alex, De Backer, Olivia, Coppola, Andrea
Language:English
en_US
Published: World Bank, Washington, DC 2015
Subjects:
WEB
BUS
GPS
URL
CAR
Online Access:http://documents.worldbank.org/curated/en/2015/08/24925779/pulse-public-opinion-using-twitter-data-analyze-public-perception-reform-el-salvador
http://hdl.handle.net/10986/22656
Description
Summary:This study uses Twitter data to provide a more nuanced understanding of the public reaction to the 2011 reform to the propane gas subsidy in El Salvador. By soliciting a small sample of manually tagged tweets, the study identifies the subject matter and sentiment of all tweets during six one-month periods over three years that concern the subsidy reform. The paper shows that such an analysis using Twitter data can provide a useful complement to existing household survey data and even potentially replace survey data if none were available. The finding show that when people tweet about the subsidy, they almost always do so in a negative manner; and there is a decline in discussion of topics about the reform subsidy, which coincides with increase in support for the subsidy as reported elsewhere. Therefore, the study concludes that decreasing discussion of the subsidy reform indicates an increase in support for the reform. In addition, the gas distributor strikes of May 2011 may have contributed to public perception of the reform more than previously acknowledged. This study is used as an opportunity to provide methodological guidance for researchers who wish to undertake similar studies, documenting the steps in the analysis pipeline with detail and noting the challenges inherent in obtaining data, classification, and inference.