Yelp Dataset Challenge Round 8 Winner
Sébastien C., Data Scientist
- Jun 23, 2017
Yelp Dataset Challenge Round 8 Winners
The eighth round of the Yelp Dataset Challenge ran throughout the first half of 2017 and, as usual, we received a large number of very impressive and interesting submissions.
Today, we are proud to announce the grand prize winner of the $5,000 award: “Clustered Model Adaption for Personalized Sentiment Analysis” by Lin Gong, Benjamin Haines, and Hongnin Wang (from the Department of Computer Science of the University of Virginia). The authors built a personalized sentiment classification model at the group level.
Their model is based on social theories about group psychology and how human beings tend to associate with similar individuals. These groups they form lead to more homogeneous opinions. Most text-based sentiment analysis models work at a global level, ignoring more “localized” group psychology and thus failing to capture the wide ranging opinions amongst users. In comparison, and partly based on their results with the Yelp dataset, the authors demonstrated that their model performs better than most. This work is fully relevant to many tech companies.
This entry was selected from many submissions for its technical and academic merit. For a full list of all previous winners of the Yelp Dataset Challenge, head over to the challenge site. Thanks to all who participated!
Dataset Example Code
We maintain a repository of example code to help you get started playing with the dataset. These examples show different ways to interact with the data and how to use our open source Python MapReduce tool mrjob with the data.
The repository includes scripts for
- Converting the dataset from JSON to CSV
- Predicting likely categories given review text
- Finishing reviews using Markov Chains
- Finding the sentiment of words in the dataset
There are many ways to explore the vast data within the Yelp Dataset Challenge Dataset. Below are some examples of some of the many cool tools that can be used with our data:
CartoDB is a cloud based mapping, analysis, and visualization engine that shows you how you can transform reviews into insightful visualizations. They wrote a blog post demonstrating how to use their tools to gain interesting insights about the Las Vegas part of the dataset.