Implementing LDA Topic Modelling Technique to Study User Reviews in Tourism
Amit Singh Chauhan, Rajni Mohana · 2022
Extracting valuable information from unstructured text is a significant difficulty in today's culture due to the ever-increasing proliferation of texts, most of which are generated via online social networks in the form of consumer-generated media. Despite this difficulty, natural language processing algorithms are being developed rapidly, including topic modelling approaches for discovering latent subjects in text documents like online reviews. As a result, topic modelling methodologies have not grown in favour of the tourist industry yet. So Authors decided to work on a tourism dataset. The results show us the importance of topic keywords concerning the tourism dataset the best perplexity score we get us with the D3 Dataset was -7.9947.