BookTubers are a rapidly growing community in YouTube who shares content related to books. Previous literature has addressed problems related to automatically analyzing opinions and mood of video logs (vlogs) as a generic category in YouTube. Unfortunately, the population studied is not diverse. In this work, we study and compare some aspects of the geographic/cultural context of BookTube videos, comparing non-western (Indian) and Western populations. The role played by nonverbal and verbal cues in each of these contexts are analyzed automatically using audio, visual, and text features. The analysis shows that cultural context and popularity can be inferred to some degree using multimodal fusion of these features. The best obtained results are an average precision-recall score of 0.98 with Random Forest in a binary India vs. Western video classification task, and 0.75 in inferring binary popularity levels of BookTube videos.