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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Oct 2, 2019
Date Accepted: Jan 27, 2020

The final, peer-reviewed published version of this preprint can be found here:

Twitter Analysis of the Nonmedical Use and Side Effects of Methylphenidate: Machine Learning Study

Kim J, Kim SC, Jeong J, Kim MG

Twitter Analysis of the Nonmedical Use and Side Effects of Methylphenidate: Machine Learning Study

J Med Internet Res 2020;22(2):e16466

DOI: 10.2196/16466

PMID: 32130160

PMCID: 7063527

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Twitter Analysis of the Nonmedical Use and Side Effects of Methylphenidate, and User Sentiment about the Drug

  • Jungu Kim; 
  • Su Cheol Kim; 
  • Jaegwon Jeong; 
  • Myeong Gyu Kim

ABSTRACT

Background:

Methylphenidate, a stimulant used to treat attention deficit hyperactivity disorder (ADHD), has the potential for nonmedical uses such as study and recreation. In the era of active use of social networking services (SNSs), experience with the nonmedical use or side effects of methylphenidate might be shared on Twitter.

Objective:

To analyze monthly tweets about methylphenidate, its nonmedical use and side effects, and user sentiments about methylphenidate.

Methods:

Tweets mentioning methylphenidate from August 2018 to July 2019 were collected using search terms for methylphenidate and its brand names. Only tweets written in English were included. The monthly number of tweets about methylphenidate and the number of tweets containing keywords related to the nonmedical use and side effects of methylphenidate were analyzed. Precision was calculated as the number of true nonmedical use or side effects divided by the number of tweets containing each keywords. Sentiment analysis was conducted using the text and emoji in tweets, and tweets were categorized as very negative (less than -3), negative (-3 to -1), neutral (0), positive (1 to 3), or very positive (more than 3), depending on the sentiment score.

Results:

A total of 4,169 tweets were ultimately selected for analysis. The number of tweets per month was lowest in August (n=264) and highest in May (n=435). There were 292 (7.0%) tweets about nonmedical uses of methylphenidate. Among those, 200 (4.8%) described use for studying, and 15 (0.4%) described use for recreation. In 91 (2.2%) tweets, snorting methylphenidate was mentioned. Side effects of methylphenidate, mainly poor appetite (n=74, 1.8%) and insomnia (n=54, 1.3%), were reported in 316 (7.6%) tweets. The average sentiment score was 0.027 ± 1.475, and neutral tweets were the most abundant (n=1,593, 38.2%).

Conclusions:

Tweets about methylphenidate were most abundant in May, mentioned nonmedical use for study or recreation, and contained information about side effects. Analysis of Twitter has the advantage of saving the cost and time needed to conduct a survey, and could help identify nonmedical uses and side effects of drugs.


 Citation

Please cite as:

Kim J, Kim SC, Jeong J, Kim MG

Twitter Analysis of the Nonmedical Use and Side Effects of Methylphenidate: Machine Learning Study

J Med Internet Res 2020;22(2):e16466

DOI: 10.2196/16466

PMID: 32130160

PMCID: 7063527

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