期刊
JOURNAL OF DRUG ISSUES
卷 49, 期 3, 页码 477-492出版社
SAGE PUBLICATIONS INC
DOI: 10.1177/0022042619833911
关键词
social media; keyword filter list; machine learning; synonym detection
资金
- National Institute on Drug Abuse of the National Institutes of Health [U01DA038360]
Social 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.
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