Crowdsourcing-Based Travel Planning Tool
Written by Xiaolu Zhou, Mingshu Wang, Dongying Li
Published on Elsevier

Crowdsourcing-Based Travel Planning Tool

🔍 Introduction: Revolutionizing Travel Planning with Crowdsourced Data

Planning a trip can be overwhelming. With countless reviews, photos, and recommendations scattered across the internet, how do you decide where to stay, what to see, and how to get there? We set out to solve this problem by creating a smart travel planning tool that uses crowdsourced data to make trip planning easier, faster, and more personalized. By combining hotel reviews from TripAdvisor, photos from Flickr, and travel costs from Uber, we built a system that not only recommends the best hotels and attractions but also optimizes your travel routes to save time and money.

🛠️ How We Did It: Mining Data for Smarter Travel

Our tool relies on three main data sources: hotel reviews, geotagged photos, and Uber ride costs. Here’s how we turned this data into actionable travel recommendations:

  • Hotel Reviews: We used natural language processing (NLP) to analyze thousands of hotel reviews from TripAdvisor. Instead of just looking at star ratings, we broke down reviews into seven key dimensions: public areas, bedroom condition, restroom condition, service, restaurant quality, location, and overall experience. This gave us a detailed picture of what each hotel does well (or not so well).
  • Tourist Attractions: We mined Flickr photos to identify popular tourist spots. By analyzing the tags, locations, and timestamps of millions of photos, we pinpointed the most visited and photographed places in Atlanta and Chicago.
  • Travel Routes: Using Uber data, we calculated the most cost-effective routes between hotels and attractions. Our algorithm considers both distance and cost to create the best travel sequences for your trip.
Sample dependency structure for hotel reviews
Figure 1: How we analyzed hotel reviews using NLP. Each sentence is broken down into its grammatical structure to identify key attributes like "clean rooms" or "friendly staff."

đź“Š What We Found: Insights from Atlanta and Chicago

We tested our tool in two major U.S. cities: Atlanta and Chicago. Here’s what we discovered:

  • Hotel Quality: Our NLP-based scoring system closely matched traditional star ratings, but with more nuance. For example, we found that service quality consistently received the highest scores, while bedroom conditions often lagged behind.
  • Popular Attractions: By analyzing Flickr photos, we identified the most photographed spots in each city. In Chicago, Millennium Park and the Art Institute topped the list, while in Atlanta, the Georgia Aquarium and Piedmont Park were crowd favorites.
  • Optimized Routes: Our route-planning algorithm reduced travel costs by up to 20% compared to traditional methods. For example, in Chicago, we found that staying near the Loop minimized Uber costs while maximizing access to top attractions.
Comparison of hotel quality scores and star ratings
Figure 2: Our NLP-based hotel quality scores (Sum) closely align with traditional star ratings (Score), but provide more detailed insights.

đź’ˇ What This Means for Travelers and Hotel Managers

Our tool isn’t just a win for travelers—it’s also a game-changer for hotel managers. By understanding how guests perceive different aspects of their properties, hotels can make targeted improvements to enhance the guest experience. For example, if a hotel scores low on bedroom condition, they might invest in better mattresses or soundproofing.

Looking ahead, we see huge potential for expanding this tool. Imagine integrating real-time data from social media or adding personalized recommendations based on your travel history. The possibilities are endless, and we’re excited to keep pushing the boundaries of what’s possible in travel planning.

Example of optimized travel routes in Chicago
Figure 3: An example of how our tool optimizes travel routes in Chicago, minimizing costs while maximizing convenience.

So, the next time you’re planning a trip, let our tool do the heavy lifting. Whether you’re exploring a new city or revisiting an old favorite, we’ll help you make the most of your adventure—one optimized route at a time.