Exploratory Data Analysis and Latent Dirichlet Allocation on Yelp Database

摘要

Exploratory data analysis plays an important role in understanding the underlying content in the data and explores statistical analysis in the form of descriptive and inferential analysis. In this paper we are taking yelp dataset and we applied exploratory data analysis to understand the features and to understand the underlying content in the dataset, from this result again we applied deep dive individual analysis on reviews given by the users on an individual entity, by using Topic modeling (Latent Dirichlet Allocation) we were able to get the frequent topics and create word cloud visualization on negative and positive words.