Tacit knowledge, unlike explicit knowledge, is not easily codifiable, yet important for machine learning models. This research explores a method to gather tacit knowledge about humor using a simple text-based party game, building on the existing idea of using games to gather tacit knowledge from crowds of people. Players propose prompts, which will then be answered by other players. They will then vote to determine which of the two answers to each prompt is the funniest. The engagement of the players with the game is measured and tacit knowledge is obtained from the jokes. With a large and diverse enough group of participants across games, a variety of tacit knowledge can be extracted.