Choosing Your Platform for Social Media Drug Research and Improving Your Keyword Filter List

被引:13
|
作者
Adams, Nikki [1 ,2 ]
Artigiani, Eleanor Erin [3 ]
Wish, Eric D. [4 ]
机构
[1] Univ Maryland, Ctr Adv Study Language, 7005 52nd Ave, College Pk, MD 20742 USA
[2] Univ Maryland, Ctr Subst Abuse Res, College Pk, MD 20742 USA
[3] Univ Maryland, Ctr Subst Abuse Res, Policy, College Pk, MD 20742 USA
[4] Univ Maryland, Ctr Subst Abuse Res CESAR, College Pk, MD 20742 USA
基金
美国国家卫生研究院;
关键词
social media; keyword filter list; machine learning; synonym detection; TWITTER DATA; CHATTER; TRENDS; DABS;
D O I
10.1177/0022042619833911
中图分类号
R194 [卫生标准、卫生检查、医药管理];
学科分类号
摘要
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.
引用
收藏
页码:477 / 492
页数:16
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