Tweeting PP: an analysis of the 2015-2016 Planned Parenthood controversy on Twitter

Discovery and characterisation of socially polarised communities on social media

Social polarisation processes have become a central phenomenon for the explanation of population behavioural dynamics in today's societies. Although recent works offer solutions for the detection of polarised political communities in social media, there is still a lack of works that allow an adequate characterization of the specific topics on which these divides between social groups are articulated. Our study aims to discover and characterise antagonistic communities on Twitter based on a method that combines the identification of authorities and textual classifiers around three public debates that have recently produced major controversies: (1) vaccination; (2) climate change; and (3) abortion. The proposed method allows the capture of polarised communities with little effort, requiring only the selection of some terms that characterise the topic and some initial authorities. Our findings show that the processes of social polarisation can vary considerably depending on the subject on which the debates are articulated. Specifically, polarisation manifests more prominently in the realms of vaccination and abortion, whereas this divide is less apparent in the context of climate change.

Examining ethno-racial attitudes of the public in Twitter discourses related to the United States Supreme Court Dobbs vs. Jackson Women's Health Organization ruling: A machine learning approach

Background

The decision of the US Supreme Court to repeal Roe vs. Wade sparked significant media attention. Although primarily related to abortion, opinions are divided about how this decision would impact disparities, especially for Black, Indigenous, and people of color. We used advanced natural language processing (NLP) techniques to examine ethno-racial contents in Twitter discourses related to the overturn of Roe vs. Wade.

Methods

We screened approximately 3 million tweets posted to Roe vs. Wade discussions and identified unique tweets in English-language that had mentions related to race, ethnicity, and racism posted between June 24 and July 10, 2022. We performed lexicon-based sentiment analysis to identify sentiment polarity and the emotions expressed in the Twitter discourse and conducted structural topic modeling to identify and examine latent themes.

Results

Of the tweets retrieved, 0.7% (n = 23,044) had mentions related to race, ethnicity, and racism. The overall sentiment polarity was negative (mean = -0.41, SD = 1.48). Approximately 60.0% (n = 12,092) expressed negative sentiments, while 39.0% (n = 81,45) expressed positive sentiments, and 3.0% (n = 619) expressed neutral sentiments. There were 20 latent themes which emerged from the topic model. The predominant topics in the discourses were related to "racial resentment" (topic 2, 11.3%), "human rights" (topic 2, 7.9%), and "socioeconomic disadvantage" (topic 16, 7.4%).

Conclusions

Our study demonstrates wide ranging ethno-racial concerns following the reversal of Roe and supports the need for active surveillance of racial and ethnic disparities in abortion access in the post-Roe era.

The Abortion Web Ecosystem: Cross-Sectional Analysis of Trustworthiness and Bias

Background

People use the internet as a primary source for learning about medical procedures and their associated safety profiles and risks. Although abortion is one of the most common procedures worldwide among women in their reproductive years, it is controversial and highly politicized. Substantial scientific evidence demonstrates that abortion is safe and does not increase a woman’s future risk for depressive disorders or infertility. The extent to which information found on the internet reflects these medical facts in a trustworthy and unbiased manner is not known.

Objective

The purpose of this study was to collate and describe the trustworthiness and political slant or bias of web-based information about abortion safety and risks of depression and infertility following abortion.

Methods

We performed a cross-sectional study of internet websites using 3 search topics: (1) is abortion safe?, (2) does abortion cause depression?, and (3) does abortion cause infertility? We used the Google Adwords tool to identify the search terms most associated with those topics and Google’s search engine to generate databases of websites related to each topic. We then classified and rated each website in terms of content slant (pro-choice, neutral, anti-choice), clarity of slant (obvious, in-between, or difficult/can’t tell), trustworthiness (rating scale of 1-5, 5=most trustworthy), type (forum, feature, scholarly article, resource page, news article, blog, or video), and top-level domain (.com, .net, .org, .edu, .gov, or international domain). We compared website characteristics by search topic (safety, depression, or infertility) using bivariate tests. We summarized trustworthiness using the median and IQR, and we used box-and-whisker plots to visually compare trustworthiness by slant and domain type.

Results

Our search methods yielded a total of 111, 120, and 85 unique sites for safety, depression, and infertility, respectively. Of all the sites (n=316), 57.3% (181/316) were neutral, 35.4% (112/316) were anti-choice, and 7.3% (23/316) were pro-choice. The median trustworthiness score was 2.7 (IQR 1.7-3.7), which did not differ significantly across topics (P=.409). Anti-choice sites were less trustworthy (median score 1.3, IQR 1.0-1.7) than neutral (median score 3.3, IQR 2.7-4.0) and pro-choice (median score 3.7, IQR 3.3-4.3) sites. Anti-choice sites were also more likely to have slant clarity that was “difficult to tell” (41/112, 36.6%) compared with neutral (25/181, 13.8%) or pro-choice (4/23, 17.4%; P<.001) sites. A negative search term used for the topic of safety (eg, “risks”) produced sites with lower trustworthiness scores than search terms with the word “safety” (median score 1.7 versus 3.7, respectively; P<.001).

Conclusions

People seeking information about the safety and potential risks of abortion are likely to encounter a substantial amount of untrustworthy and slanted/biased abortion information. Anti-choice sites are prevalent, often difficult to identify as anti-choice, and less trustworthy than neutral or pro-choice sites. Web searches may lead the public to believe abortion is riskier than it is.