Text-as-data methods have revolutionized the study of political behavior and human communication more generally, and the increasing availability of multilingual text collections promises exciting new applications of these methods in comparative research. To encourage researchers to seize these opportunities, we provide a guide to multilingual quantitative text analysis. We first discuss common challenges researchers face when dealing with multilingual text corpora, including concerns about resource requirements, limits to translatability, and the measurement of context-dependent concepts. We then discuss reasons for why it can nevertheless be worthwhile to go cross-lingual in applied research. We complement this discussion with a systematic overview of multilingual text analysis methods developed for political science and communication research, focusing on cross-lingual dictionary analysis, supervised text classification, topic modeling, and text scaling. To structure this overview, we distinguish between output alignment, bridging, and input alignment approaches to cross-lingual text analysis and thus integrate existing methods into a common framework that provides orientation in a very active field of research. We conclude with an outlook on future directions for method development and potential fields of applications.