Sentimantle

Sentiment Analysis Dashboard for Properties
Role
Web Scraping, Automation, Machine Learning, Back-end Development, Front-end Development
Project Goal
Sentimantle is an advanced sentiment analysis tool designed to assist property owners and managers understand the feedback and sentiments expressed in reviews from well-known platforms. The system consists of two dashboards: an Admin dashboard for controlling activities and a User dashboard where users can sign up, add properties, and generate comprehensive sentiment analysis reports.
Challenge
The main challenge was to create an automated system that could scrape reviews from Google Maps, Booking.com, and TripAdvisor for various properties, analyze the sentiment of these reviews using machine learning algorithms, and present the results in an understandable and useful manner. Additionally, the system needed to support various user operations such as creating reports, comparing them, and setting up alerts for negative feedback.
Publish date
march 15, 2024
Project type
Analysis Dashboard for Properties

Skills and Deliverables

  • Web Scraping:
    Extracting reviews from Google Maps, Booking.com, and TripAdvisor.
  • Automation: Automating the data extraction and report generation processes.
  • Machine Learning: Implementing sentiment analysis and aspect-based sentiment analysis algorithms.
  • Back-end Development: Building the infrastructure to support user sign-ups, property management, and report generation.
  • Front-end Development: Designing and developing the dashboard to visualize data and reports

Solution

To tackle the challenge, we developed a two-dashboard in system:

Admin Dashboard

The Admin dashboard provides tools for tracking user activities, monitoring data flow, and ensuring the system operates smoothly. Admins can manage all properties, reviews, and reports generated by users.

User Dashboard

The User dashboard allows property owners/managers to sign up and add properties. The system then searches for these properties on Google Maps, Booking.com, and TripAdvisor, scraping relevant reviews. The reviews are analyzed using machine learning algorithms to determine the sentiment (positive, negative, or neutral) and identify key aspects and their positions.
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Contact info
Islamabad,Pkaistan
+92 331 000000
info@codeaza.org
At Codeaza, we're not just about providing services—we're about empowering businesses to thrive in the digital age. Let us be your partner in success, and together, we'll revolutionize your data journey.sem vel tellus ultrices ac suscipit orci
Contact info
Islamabad,Pkaistan
+92 331 000000
info@codeaza.org