teju163dst / Sydney-NSW-Airbnb-reviews-

The goal of this project is to conduct a comprehensive Time Series Topic Tracking Analysis on Airbnb reviews, with the aim of extracting valuable insights into the temporal dynamics of user sentiments, preferences, and emerging trends.

Sydney-NSW-Airbnb-reviews-

The goal of this project is to conduct a comprehensive Time Series Topic Tracking Analysis on Airbnb reviews, with the aim of extracting valuable insights into the temporal dynamics of user sentiments, preferences, and emerging trends. I received this use case from a client that approached me via Fiverr for their ongoing project. I have permission to share my POCs without the dataset.

Data Collection: Gather Airbnb review data, including timestamps, ratings, and textual content.

Preprocessing: Clean and preprocess the data, including text tokenization, removal of stop words, and handling missing values.

Time Series Analysis: Apply statistical methods and machine learning techniques for time series analysis of reviews.

Topic Modeling: Implement topic modeling algorithms to extract latent topics from the textual data.

Sentiment Analysis: Utilize sentiment analysis techniques to categorize reviews into positive, negative, or neutral sentiments.

Visualization and Reporting: Create visualizations and reports to effectively communicate findings.