Project Summary Everybody’s Google is a web browser extension which mines personalized Google search results and redistributes them to extension users when search queries are executed, allowing them to see the various (personalized) perspectives Google creates of its own “world model.”

Goals To raise awareness of web personalization by showing the physical evidence of its existence To use this data “reverse-engineer” user models. (Reverse engineering from this data will likely be impossible, but it should clearly demonstrate some of the things Google knows about each individual)

What’s Been Done Seed program with “politically charged” and/or ambiguous phrases Perform searches on those phrases and compare my own personalized search results with the “baseline” (un-personalized) Google search results

Current State It’s buggy, but it works The server stores all searches ever done by users with the plug-in installed (privacy issues?) If another user has executed the same query as you, a sidebar appears on Google results page with all other users’ results The server also generates non-personalized, “baseline” search results for queries in the system (up to 100/day)

Video Demo (*there are a few pauses when my debugger comes up – it’s actually not as slow as it seems at first.)

Problems Personalization only works with things you’ve searched for or clicked on before – politically charged phrases don’t make great seeds What to do about specialized Google search results? (News, shopping, travel, stocks, etc.) It will break if Google changes its web page markup (unsure if this will work on foreign Google home pages) Various bugs still need to be worked out Potential privacy concerns (AOL search release)

Next Steps Clean interface Fix bugs Add Firefox (& Safari) Create link to website which will allow random browsing of results listings Find users!

Future Usage The data does not capture or track any PII data (aside from search queries), but could ask for people to opt-in and volunteer demographic information to overlay on top of this dataset Would be great to run various NLP algorithms (sentiment analysis, political stance) to attempt to reverse-engineer Google’s “user models”

Personalization Eventually I will be mining the personalized search results returned to individual users The data being collected this quarter can serve as a “baseline” for non-personalized search results for this class I hope to compare “baseline” with my own personal searches