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Introduction Although debate remains about the saliency and relevance of pro‐choice and pro‐life labels (as abortion belief indicators), they have been consistently used for decades to broadly designate abortion identity. However, clear labels are less apparent in other languages (e.g., Spanish). Social media, as an exploratory data science tool, can be leveraged to identify the presence and popularity of online abortion identity labels and how they are contextualized online. Purpose This study aims to determine how popularly used Spanish‐language pro‐choice and pro‐life identity labels are contextualized online. Method We used Latent Dirichlet Allocation (LDA) topic models, an unsupervised natural language processing (NLP) application, to generate themes about Spanish language tweets categorized by Spanish abortion identity labels: (1) proelección (pro‐choice); (2) derecho a decidir (right to choose); (3) proaborto (pro‐abortion); (4) provida (pro‐life); (5) antiaborto (anti‐abortion); and (6) derecho a vivir (right to life). We manually reviewed themes for each identity label to assess scope. Results All six identity labels included in our analysis contained some references to abortion. However, several labels were not exclusive to abortion. Proelección (pro‐choice), for example, contained several themes related to ongoing presidential elections. Discussion and Conclusion No singular Spanish abortion identity label encapsulates abortion beliefs; however, there are several viable options. Just as the debate remains ongoing about pro‐choice and pro‐life as accurate indicators of abortion beliefs in English, we must also consider that identity is more complex than binary labels in Spanish.

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Introduction Although much work has been done on US abortion ideology, less is known relative to the psychological processes that distinguish personal abortion beliefs or how those beliefs are communicated to others. As part of a forthcoming probability-based sampling designed study on US abortion climate, we piloted a study with a controlled sample to determine whether psychological indicators guiding abortion beliefs can be meaningfully extracted from qualitative interviews using natural language processing (NLP) substring matching. Of particular interest to this study is the presence of cognitive distortions—markers of rigid thinking—spoken during interviews and how cognitive distortion frequency may be tied to rigid, or firm, abortion beliefs. Methods We ran qualitative interview transcripts against two lexicons. The first lexicon, the cognitive distortion schemata (CDS), was applied to identify cognitive distortion n-grams (a series of words) embedded within the qualitative interviews. The second lexicon, the Linguistic Inquiry Word Count (LIWC), was applied to extract other psychological indicators, including the degrees of (1) analytic thinking, (2) emotional reasoning, (3) authenticity, and (4) clout. Results People with polarized abortion views (i.e., strongly supportive of or opposed to abortion) had the highest observed usage of CDS n-grams, scored highest on authenticity, and lowest on analytic thinking. By contrast, people with moderate or uncertain abortion views (i.e., people holding more complex or nuanced views of abortion) spoke with the least CDS n-grams and scored slightly higher on analytic thinking. Discussion and conclusion Our findings suggest people communicate about abortion differently depending on their personal abortion ideology. Those with strong abortion views may be more likely to communicate with authoritative words and patterns of words indicative of cognitive distortions—or limited complexity in belief systems. Those with moderate views are more likely to speak in conflicting terms and patterns of words that are flexible and open to change—or high complexity in belief systems. These findings suggest it is possible to extract psychological indicators with NLP from qualitative interviews about abortion. Findings from this study will help refine our protocol ahead of full-study launch.