Cross-Domain Consumer Review Analysis
This work addresses the need for cross-domain insights into customer satisfaction and engagement, but it is incremental as it applies existing methods to new datasets without novel methodological contributions.
The paper tackled the problem of analyzing consumer reviews across four domains (Amazon, Yelp, Steam, IMDb) to uncover trends in sales and customer sentiment, processing nearly 12 million reviews using Hadoop and Spark for scalability.
The paper presents a cross-domain review analysis on four popular review datasets: Amazon, Yelp, Steam, IMDb. The analysis is performed using Hadoop and Spark, which allows for efficient and scalable processing of large datasets. By examining close to 12 million reviews from these four online forums, we hope to uncover interesting trends in sales and customer sentiment over the years. Our analysis will include a study of the number of reviews and their distribution over time, as well as an examination of the relationship between various review attributes such as upvotes, creation time, rating, and sentiment. By comparing the reviews across different domains, we hope to gain insight into the factors that drive customer satisfaction and engagement in different product categories.