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Updated: Aug 9, 2025

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
Trends in stigmatizing language about addiction: A longitudinal analysis of multiple public communication channels
Nilay McLaren1, Christopher M Jones2, Rita Noonan2
1Columbia University, New York City, NY, United States; National Center for Injury Prevention and Control, US Centers for Disease Control and Prevention, Atlanta, GA, United States.
Introduction:
Stigma associated with substance use and addiction is a major barrier to overdose prevention. Although stigma reduction is a key goal of federal strategies to prevent overdose, there is limited data to assess progress made in reducing use of stigmatizing language about addiction.
Methods:
Using language guidelines published by the federal National Institute on Drug Abuse (NIDA), we examined trends in use of stigmatizing terms about addiction across four popular public communication modalities: news articles, blogs, Twitter, and Reddit. We calculate percent changes in the rates of articles/posts using stigmatizing terms over a five-year period (2017-2021) by fitting a linear trendline and assess statistically significant trends using the Mann-Kendall test.
Results:
The rate of articles containing stigmatizing language decreased over the past five years for news articles (-68.2 %, p < 0.001) and blogs (-33.6 %, p < 0.001). Among social media platforms, the rate of posts using stigmatizing language increased (Twitter [43.5 %, p = 0.01]) or remained stable (Reddit [3.1 %, p = 0.29]). In absolute terms, news articles had the highest rate of articles containing stigmatizing terms over the five-year period (324.9 articles per million) compared to 132.3, 18.3, and 138.6 posts per million for blogs, Twitter, and Reddit, respectively.
Conclusions:
Use of stigmatizing language about addiction appears to have decreased across more traditional, longer-format communication modalities such as news articles. Additional work is needed to reduce use of stigmatizing language on social media.
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