Understanding Topic Coherence Measures

Topic Modeling is one of the most important NLP fields. It aims to explain a textual dataset by decomposing it into two distributions: topics and words. So, a Topic Modeling Algorithm is a mathematical/statistical model used to infer what are the topics that better represent the data. For simplicity, a topic can be described as a collection of words, like ['ball', 'cat', 'house'] and ['airplane', 'clouds'], but in practice, what an algorithm does is assign each word in our vocabulary a'participation' value in a given topic. The words with the highest values can be considered as the true participants of a topic.