Paper Info
Title
Predicting public opinion on drug legalization - social media analysis and consumption trends.
Abstract
In this paper, we focus on the collection and analysis of relevant Twitter data on a state-by-state basis for (i) measuring public opinion on marijuana legalization by mining sentiment in Twitter data and (ii) determining the usage trends for six distinct types of marijuana. We overcome the challenges posed by the informal and ungrammatical nature of tweets to analyze a corpus of 306,835 relevant tweets collected over the four-month period, preceding the November 2015 Ohio Marijuana Legalization ballot and the four months after the election for all states in the US. Our analysis revealed two key insights: (i) the people in states that have legalized recreational marijuana express greater positive sentiments about marijuana than the people in states that have either legalized medicinal marijuana or have not legalized marijuana at all; (ii) the states that have a high percentage of positive sentiment about marijuana is more inclined to authorize (e.g., by allowing medical marijuana) or broaden its legal usage (e.g., by allowing recreational marijuana in addition to medical marijuana). Our analysis shows that social media can provide reliable information and can serve as an alternative to traditional polling of public opinion on drug use and epidemiology research.
Year
DOI
Venue
2019
10.1145/3341161.3344380
ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining Vancouver British Columbia Canada August, 2019
Keywords
DocType
ISBN
Marijuana Legalization, Drug Abuse Ontology, Public Opinion, Sentiment Analysis, Prediction, Consumption Trends, Entity Extraction, Machine Learning
Conference
978-1-4503-6868-1
Citations 
PageRank 
References 
0
0.34
2
Authors
5
Name
Order
Citations
PageRank
Farahnaz Golrooy Motlagh100.34
Saeedeh Shekarpour2403.70
Amit P. Sheth3109501885.56
Krishnaprasad Thirunarayan469686.55
michael l raymer57011.20