This dissertation has three stand-alone articles that provide methodological and substantive advances to studying American politics. The introductory section introduces group identity in political science and social science. In "Bayesian Multilevel Models for Intersections of Race, Gender, and Class," I update the functional form of intersectionality to provide a modeling approach that better performs in small sample size environments common in historical survey data. The second article, "The Identity-Based Determinants of Voter Confidence," shows how racial attitudes and group identity frame confidence in election integrity in 2020 and how the Bayesian Multilevel Model can be used to study small but influential subsets of voters. The final article, "The Duality of Gender Consciousness in the Dobbs v. Jackson Era," shows substantively how complicated gender consciousness is in the context of abortion on social media as opposed to exclusively feminist consciousness, as seen in #MeToo. Further, this work provides methodological advances in user-generated content as another avenue to study political psychology concepts in public opinion.