MIMS Final Project 2012

Grepvine

Grepvine

 

Better Discussions

Find comments and articles related to the content you already care about. Find better discussions!

 

Related Comments

We have a team of solr monkeys working hard to provide you with comments related to the article you are currently reading.

 

Related Articles

Our team of solr monkeys reads articles from Mashable, Wired and Engadget. These monkeys tell us which articles are related to the one you are reading.

 

Filters

Use filters to reveal richer comments and articles.

 

Team

Our team is made up of three lucene cowboys UC Berkeley Masters of Information and 100 solr monkeys. The monkeys don't have names. Our names are Ram Joshi, Chulki Lee, and Walter Koning.

 

Advisor

The Grepvine team has been advised by Coye Cheshire.

grepvine.jpg

Information Overload

There is too much duplication of content, especially on popular current events in technology and politics. User comments can be helpful to gauge opinion. Aggregation sites use a public voting system to promote the best information to the top. We want to bring the benefits of such systems to the larger internet audience.

No ideal way to find online discussion

There is no exclusive search for online comments and opinions. Search engines treat comments as part of the text on web pages. There is no curation.

Search bubble

Content is carefully customized to user preferences and there is a growing concern of a search bubble. We believe that a free flow of online discussions is one of the ways to escape this trend. Current tools limit free exploration.

Last updated:

October 7, 2016