Star Quality: Aggregating Reviews to Rank Products and Merchants

author: Mary McGlohon, School of Computer Science, Carnegie Mellon University
published: June 29, 2010,   recorded: May 2010,   views: 3689
Categories

See Also:

Download slides icon Download slides: icwsm2010_mcglohon_arr_01.pdf (1.1┬áMB)


Help icon Streaming Video Help

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

Given a set of reviews of products or merchants from a wide range of authors and several reviews websites, how can we measure the true quality of the product or merchant? How do we remove the bias of individual authors or sources? How do we compare reviews obtained from different websites, where ratings may be on different scales (1-5 stars, A/B/C, etc.)? How do we filter out unreliable reviews to use only the ones with "star quality"? Taking into account these considerations, we analyze data sets from a variety of different reviews sites (the first paper, to our knowledge, to do this). These data sets include 8 million product reviews and 1.5 million merchant reviews. We explore statistic - and heuristic - based models for estimating the true quality of a product or merchant, and compare the performance of these estimators on the task of ranking pairs of objects. We also apply the same models to the task of using Netflix ratings data to rank pairs of movies, and discover that the performance of the different models is surprisingly similar on this data set.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: