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Choosing your platform for social media drug research and improving your keyword filter list

dc.contributor.authorAdams, Nikki
dc.contributor.authorArtigiani, Eleanor Erin
dc.contributor.authorWish, Eric D.
dc.description.abstractSocial media research often has two things in common: Twitter is the platform used and a keyword filter list is used to extract only relevant Tweets. Here we propose that (a) alternative platforms be considered more often when doing social media research, and (b) regardless of platform, researchers use word embeddings as a type of synonym discovery to improve their keyword filter list, both of which lead to more relevant data. We demonstrate the benefit of these proposals by comparing how successful our synonym discovery method is at finding terms for marijuana and select opioids on Twitter versus a platform that can be filtered by topic, Reddit. We also find words that are not on the U.S. Drug Enforcement Agency (DEA) drug slang list for that year, some of which appear on the list the subsequent year, showing that this method could be employed to find drug terms faster than traditional means.en_US
dc.description.sponsorshipResearch reported in this publication was supported by the National Institute on Drug Abuse of the National Institutes of Health under Award Number U01DA038360 awarded to the Center for Substance Abuse Research (CESAR) at the University of Maryland, College Park.en_US
dc.subjectsocial media, keyword filter list, machine learning, synonym detectionen_US
dc.titleChoosing your platform for social media drug research and improving your keyword filter listen_US
dc.relation.isAvailableAtCenter for Advanced Study of Language
dc.relation.isAvailableAtDigitial Repository at the University of Maryland
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md)

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