Content analysis is one of the core methods of communication science. However, it is currently confronted with several challenges, such as the influx of procedures, data, and measurements emerging from computational methods. To understand how communi- cation science adapts its methods while simultaneously reassuring their ongoing function- ality, the six contributions in this Special Issue focus on (re)established quality criteria for content analysis. They showcase the fact that while manual content analysis (and human coders) is still at the core of our methodology, traditional quality criteria are being reinter- preted and approximated, often in light of open science practices and computational text analysis. Therefore, we call for further reflection on conceptual clarity and methodological approaches related to traditional quality criteria (validity, reliability), how they may be reestablished (reproducibility, robustness, and replicability), as well as criteria that have recently come into focus (e.g., ethics). By bringing together leading scholars in this Special Issue, we aim to contribute to moving content analysis forward as a method based on in- sights from both inside and outside our discipline.