Currently submitted to: Journal of Medical Internet Research
Date Submitted: Feb 17, 2025
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited.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.
Using Natural Language Processing to describe use of r/abortion: A dynamic topic approach to analyzing Reddit post data from an online community for abortion during 2022
ABSTRACT
Background:
Abortion access in the United States (US) has been in a state of rapid change and increasing restriction since the Dobbs v. Jackson Women’s Health Organization decision in June of 2022. With further constraints on access to abortion since Dobbs, the internet and online communities are playing an increasingly important role in people’s abortion trajectories. There is a need for a broader understanding of how online resources are used for abortion and how they may reflect changes in the socio-political and legal context of abortion access. Research using online information and leveraging methods to work efficiently with large datasets has the potential to accelerate knowledge generation and provide novel insights into changing abortion-related experiences following Dobbs, helping to address these gaps.
Objective:
This project sought to use Natural Language Processing (NLP) techniques, specifically topic modeling, to explore the content of posts to one online community for abortion (r/abortion) in 2022 and assess if community use changed during that time.
Methods:
This analysis describes and explores posts shared throughout the entire year and for three sub-periods of interest: pre-Dobbs-leak (12/24/2021-5/01/2022), Dobbs-leak to decision (5/02/2022-6/23/2022), and post-Dobbs-decision (6/24/2022-12/23/2022). We used BERTopic to determine topic models for the year and each sub-period and then classify posts into topics. Topics were then aggregated into ‘conceptual groups’ based on a combination of quantitative and qualitative assessments. Classification counts of posts in each conceptual group were used to assess change in the commonality of posts per topic throughout the year.
Results:
In the 7,273 posts shared in r/abortion in 2022 included in our analyses, we found that people posted seeking pathways to access abortion, support in managing their abortion process during and after having an abortion, community input on pregnancy confirmation, assessment of abortion completion and normalcy/safety of post-abortion experiences, and describing and sometimes seeking input on abortion decision-making. We also found that while posts about all conceptual groups increased following the Dobbs decision (p<0.001 for all), the greatest percent increase was in posts related to self-managed abortion.
Conclusions:
This analysis provides a holistic view of the content of text submissions to r/abortion in 2022, highlighting the important role of online communities as abortion-supportive online resources. As policies and pathways to abortion access continue to change across the US, approaches leveraging NLP with sufficiently large samples of textual data present opportunities for timely monitoring with the potential to reflect a broad range of abortion experiences, including those of people who have limited or no interaction with clinical abortion care. Clinical Trial: N/A
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