“…The former task assesses content; it detects and labels objects in images, finds people and their faces, infers humans' attributes (e.g., ethnicity, age) and expressions (e.g., emotion, ideology), and so on. It is usually done by building on the manual coding of concepts within and across observations (e.g., Casas and Williams 2019;Trilló and Shifman 2021; van Haperen, Uitermark, and van der Zeeuw 2020), using machine learning (ML) methods (e.g., Cantú 2019;Steinert-Threlkeld, Chan, and Joo 2021;Xi et al 2020;Zhang and Pan 2019), or a combination of the two, such as by first doing manual coding to uncover concepts-and examples of these concepts-that are then used in ML-driven analysis (e.g., Steinert-Threlkeld and Joo 2020;Steinert-Threlkeld et al 2021;van Haperen et al 2020). 2 After identifying and measuring relevant dimensions of images, researchers usually then classify all the images in the database using a framework relevant to their research questions.…”