Low-code tools play an important role in making data analysis and visualization accessible to researchers and students with limited experience, or interest, in programming. While low-code tools do introduce closedbox issues, they can still be considered important stepping stones toward computational approaches. This chapter draws on two such tools, Octoparse and KNIME (Konstanz Information Miner), to present a workflow from data collection from online sources, through text pre-processing, toward text classification in the context of the ongoing project Cultural Institutions and the Culture War (CICuW) that investigates the democratic implications of the pervasiveness of farright digital discourse. This chapter will introduce web scraping, topic modeling, and sentiment analysis in an accessible way, while also showcasing state-of-the-art approaches to the analysis components through the use of BERT (Bidirectional Encoder Representations from Transformers) models and zero-shot classification. The chapter will take a critical perspective on the described methods by discussing how they contribute to creating methodological closed-boxes and how quantitative techniques can be fruitfully combined with qualitative approaches.