imyaash / Tourist-Accomodation-Review-Sentiment-Analysis-and-Text-Mining

This code performs sentiment analysis on a dataset of tourist accommodation reviews. The dataset, tourist_accommodation_reviews.csv, is provided alongside this code.

Tourist Accommodation Review Sentiment Analysis

This code performs sentiment analysis on a dataset of tourist accommodation reviews. The dataset, tourist_accommodation_reviews.csv, is provided alongside this code.

Requirements

pandas
matplotlib
seaborn
wordcloud
nltk

Getting Started

Download and install the required libraries.
Download the stopwords, punkt, wordnet, omw-1.4, and vader_lexicon NLTK corpora by running nltk.download(["stopwords", "punkt", "wordnet", "omw-1.4", "vader_lexicon"]).
Run the code to perform sentiment analysis on the reviews in the dataset.

Functions

mostReviewedHotels(df) This function takes a dataframe as input and filters it to only include the 30 hotels with the most reviews.

reviewAnalyzer(sia, reviews) This function takes a SentimentIntensityAnalyzer object and a list of reviews as input and returns four lists containing the compound, negative, neutral, and positive sentiment scores for each review.

Results

The code calculates some basic statistics for the sentiment score columns and creates four histograms to visualize the distribution of the sentiment scores.