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Predicting public opinion on drug legalization: social media analysis and consumption trends

Authors:

Farahnaz Golrooy Motlagh,

Saeedeh Shekarpour,

Krishnaprasad Thirunarayan,

Michael L. RaymerAuthors Info & Claims

ASONAM '19: Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

Pages 952 - 961

https://doi.org/10.1145/3341161.3344380

Published: 15 January 2020 Publication History

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.

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Cited By

Lokala ULamy FDaniulaityte RGaur MGyrard AThirunarayan KKursuncu USheth A(2020)Drug Abuse Ontology to Harness Web-Based Data for Substance Use Epidemiology Research: Ontology Development Study (Preprint)JMIR Public Health and Surveillance10.2196/24938Online publication date: 10-Oct-2020
https://doi.org/10.2196/24938

Predicting public opinion on drug legalization: social media analysis and consumption trends
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms

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Published In

cover image ACM Conferences

ASONAM '19: Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

August 2019

1228 pages

ISBN:9781450368681

DOI:10.1145/3341161

Editors:
Francesca Spezzano
Boise State University
,
Wei Chen
Microsoft Research, China
,
Xiaokui Xiao
National University of Singapore, Singapore

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 15 January 2020

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National Institute on Drug Abuse (NIDA)
National Science Foundation

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ASONAM '19

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SIGKDD

ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining

August 27 - 30, 2019

British Columbia, Vancouver, Canada

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ASONAM '19 Paper Acceptance Rate 41 of 286 submissions, 14%;

Overall Acceptance Rate 116 of 549 submissions, 21%

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Cited By

Lokala ULamy FDaniulaityte RGaur MGyrard AThirunarayan KKursuncu USheth A(2020)Drug Abuse Ontology to Harness Web-Based Data for Substance Use Epidemiology Research: Ontology Development Study (Preprint)JMIR Public Health and Surveillance10.2196/24938Online publication date: 10-Oct-2020
https://doi.org/10.2196/24938

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