1 / 10

Diabeat.us

Diabeat.us. Diabetes lifestyle management Andrew Alles Victor Benjamin Robert Erikson Xiao Liu. Introduction. With the emergence of web 2.0, individuals have been heavily using the Internet to share ideas and experiences

sasson
Télécharger la présentation

Diabeat.us

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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 • 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 • Requires users to visit multiple sources • Poor organization can make content hard to find

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

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

  5. Competitor Analysis • Much overlap exists between currently existing web communities • 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.

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

  7. Architectural Components • Web Design and Hosting • Amazon EC2 • Apache Tomcat • Windows Server 2008 • MSSQL 2008 • APIs • Twitter • Google Adsense, Feed, Search • Google Android • Amazon • Facebook • Youtube • Wikipedia • Flickr • 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 • Sentiment analysis on drug and treatments can quickly let patients know how others experience and feel various treatments

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

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

More Related