I'm doing a student project where I construct a model predicting the number of languages that a given Wikipedia article is translated into (for example, the article TOYOTA is translated into 93 languages). I've tried extracting basic info (article length, number of links, etc.) to create a simple regression model, but can't get the $R^2$ value above $0.25$ or so.
What's the most appropriate NLP algorithm for regression problems? Almost all examples I find online are classification problems. FYI I'm aware of the basics of NLP preprocessing (tokenization, lemmatization, bag of words, etc).