1. Diabeat.us Diabetes lifestyle management Andrew Alles Victor Benjamin Robert Erikson Xiao Liu

2. Introduction With the emergence of web 2.0, individuals have been heavily using the Internet to share ideas and experiences With the emergence of web 2.0, individuals have been heavily using the Internet to share ideas and experiences In particular, support groups are quite prominent and useful to Internet users, especially concerning medical problems In particular, support groups are quite prominent and useful to Internet users, especially concerning medical problems However, much of the content existing on the Internet today is disjointed However, much of the content existing on the Internet today is disjointed Requires users to visit multiple sources Requires users to visit multiple sources Poor organization can make content hard to find Poor organization can make content hard to find

3. Objectives Diabeat.us seeks to advance the accessibility of diabetes related resources to Internet users Diabeat.us seeks to advance the accessibility of diabetes related resources to Internet users Diabetes related news and recipes Diabetes related news and recipes Educational books and videos Educational books and videos Web community analytics Web community analytics Content represented must come from a set of diverse, yet credible information sources Content represented must come from a set of diverse, yet credible information sources Current leading diabetes information sources (e.g. diabetes.org) Current leading diabetes information sources (e.g. diabetes.org) Various popular web APIs contribute content and form Various popular web APIs contribute content and form Information visualized from patient-generated web content Information visualized from patient-generated web content

4. What’s so special? Functionalities Functionalities Meta-search across multiple renown diabetes resources Meta-search across multiple renown diabetes resources Nutritional Information, Recipes Nutritional Information, Recipes News, Research Progress News, Research Progress Videos, Multimedia Videos, Multimedia Social media analytics Social media analytics Sentiment analysis on potential diabetes treatments Sentiment analysis on potential diabetes treatments Social network analysis to identify credible and helpful individuals in diabetes support communities Social network analysis to identify credible and helpful individuals in diabetes support communities

5. Competitor Analysis Much overlap exists between currently existing web communities Much overlap exists between currently existing web communities However, analysis of user generated content is not featured However, analysis of user generated content is not featured Such analysis could benefit patients by quickly assessing the opinions and experiences of entire web communities. It gives us an edge where competitors cannot “diabeat” us. Such analysis could benefit patients by quickly assessing the opinions and experiences of entire web communities. It gives us an edge where competitors cannot “diabeat” us. WebsiteBasic Diabetes Information NewsRecipesMultimediaDrug Sentiment Analysis Social Network Analysis Diabetes.org √√√√XX Diabetes.co.uk √√√√XX Dlife.com √√√√XX Diabeat.us √√√√√√

6. Business Models Advertisement Advertisement Google Adsense Google Adsense Amazon Referrals Amazon Referrals Youtube Channel Partnership Youtube Channel Partnership Subscription-based content Subscription-based content Sentiment analysis of treatment discussions Sentiment analysis of treatment discussions Social network analysis of web communities Social network analysis of web communities

7. Architectural Components Web Design and Hosting Web Design and Hosting Amazon EC2 Amazon EC2 Apache Tomcat Apache Tomcat Windows Server 2008 Windows Server 2008 MSSQL 2008 MSSQL 2008 APIs APIs Twitter Twitter Google Adsense, Feed, Search Google Adsense, Feed, Search Google Android Google Android Amazon Amazon Facebook Facebook Youtube Youtube Wikipedia Wikipedia Flickr Flickr IBM Many Eyes (SNA Visualization) IBM Many Eyes (SNA Visualization)

8. Analytics and Novelty We perform text mining of user-generated web content to quickly assess what people are saying about diabetes We perform text mining of user-generated web content to quickly assess what people are saying about diabetes Sentiment analysis on drug and treatments can quickly let patients know how others experience and feel various treatments Sentiment analysis on drug and treatments can quickly let patients know how others experience and feel various treatments

9. Member Contributions Member Contributions Member Contributions Andrew Alles – Server Admin, App development Andrew Alles – Server Admin, App development Victor Benjamin – Web and backend programming Victor Benjamin – Web and backend programming Robert Erikson – API research and implementation Robert Erikson – API research and implementation Xiao Liu – Analytics and API programming Xiao Liu – Analytics and API programming All members assisted each other with various tasks All members assisted each other with various tasks Each member participated in collection and extracting existing web content Each member participated in collection and extracting existing web content Bug fixes and design changes handled collectively Bug fixes and design changes handled collectively

10. Future Future Future Advance analytic services and content Advance analytic services and content Expand website to include Chinese content Expand website to include Chinese content Development of analytics for Chinese content Development of analytics for Chinese content Establish better social media presence Establish better social media presence