NLP and opinion analysis from TripAdvisor reviews in spanish about peruvian Restaurant Tanta

Built a Flask web application of TripAdvisor attraction data analyzer, the user can enter the URL link of an attraction on TripAdvisor and have the review data analyzed instantly with sentiment analysis, built with Python, selenium and NLP

NLP Sentiment analysis & modeling of Tripadvisor hortel reviews.

TripAdvisor's NLP analysis in Portuguese

TripAdvisor Sentiment Analysis using NLP and Machine Learning This project analyzes TripAdvisor reviews to predict user sentiment (1–5 ratings) using text preprocessing, TF-IDF vectorization, SMOTE for balancing, and Random Forest for classification.

IE 2nd term project prototype application based on Telefonica Mobility and BBVA Credit Card Payments. Provider data is strictly disclosed; but you can use the code in any purpose you desire. MVC stack framework using python Django. Api integrations with Expedia and Twitter Streaming API. Important work on TripAdvisor webscraping. NLP (NLTK) for Topic based sentiment analysis(Trip Advisor Reviews), Timeseries forecasting, Recommendation Engine, Leaflet Data Visualization, NetworkX SNA (python and JS). BBVA data is neglected because of lack of data integrity and necessary categories. I hope this work can be helpful to practicioners of Django framework and analytics. This application is developed in a very short term with Agile methodology, therefore it is normal that there are problems and inconsistencies of code quality. For example we tried to use mongoengine and Django framework document models as a common data source; but we faced with difficulties time to time because of lack of accurate documentation in web. Whenever we resolved we followed the accurate coding practice. Please followup the model usage practice in the last view in views.py to comply with MVC, do not use pymongo directly. Mongoengine will provide features like DBConnectionPooling that will facilitate a scalable architecture.

TripAdvisor web scrapping, text classification with ML algorithms and sentiment analysis with NLP.

Sentiment Analysis and Prediction on TripAdvisor Hotel Reviews with Natural Language Processing (NLP) and Deep Learning

Bi-directional LSTM used on Hotel Reviews from TripAdvisor for NLP analysis.

NLP analysis TripAdvisor

This project utilizes several NLP techniques, including tokenization, stopword removal, stemming, and sentiment analysis.

As part of my MSc coursework, I conducted a full-stack sentiment analysis pipeline on over 5,300 user-generated hotel reviews scraped from TripAdvisor (covering 120+ Sri Lankan hotels). This project was designed to support tourism revival by highlighting customer sentiments toward popular destinations.

NLP Analysis on Tripadvisor Restaurant Reviews

NLP_Analysis TripAdvisor Hotel Reviews Dataset

Lyon Restaurant Reviews Analysis on Trip Advisor using NLP

Using Natural Language Processing for Sentimental Analysis on TripAdvisor Dataset from Kaggle

NLP analysis on Reviews left on TripAdvisor for restaurants

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Latent Dirichlet Allocation – on TripAdvisor Reviews for Topic Extraction

NLP project doing sentiment analysis on Asos Tripadvisor reviews

Sentiment Analysis and Prediction using NLP on TripAdvisor Dataset.

In this project, the main task is determining whether the sentiment contained in a hotel review can reliably predict its rating. The problem addressed in this project is to determine if machine learning techniques can accurately group hotel review sentiment based on textual content alone.

Just a Natural Language Processing (NLP) simple Sentiment Analysis (SA) on tripadvisor hotel reviews csv dataset

NLP-based sentiment analysis model that predicts the sentiment (positive, negative, or neutral) of TripAdvisor hotel reviews.

A Python-based NLP preprocessing pipeline using NLTK and Pandas to clean and structure TripAdvisor hotel reviews for sentiment analysis and text modeling.

This is a Las Vegas TripAdvisor Dataset on which NLP is performed. Processes like Pre-processing of the data, Sentiment Analysis and Topic modeling using LDA are executed.

Sentiment analysis of TripAdvisor reviews to support tourism promotion in Namibia. Includes data collection, preprocessing, sentiment classification (VADER, SVM, RoBERTa), model evaluation, and insights using NLP and machine learning techniques.

Group project by Digital Linguistics students from the Faculty of Humanities and Social Sciences, University of Zagreb, as part of the NLP course. The project focuses on performing sentiment analysis of TripAdvisor reviews.

This project implements a sentiment analysis pipeline to classify hotel reviews from TripAdvisor into rating categories. It utilizes natural language processing (NLP) techniques for text cleaning and a Logistic Regression model for multi-class classification.

This project analyzes TripAdvisor reviews using NLP to classify sentences by sentiment and identify high-frequency positive and negative terms. It surfaces actionable insights through word frequency and probability analysis, helping businesses improve customer experience.