Abstract
Surveys show that around 70% of US Internet users consult the Internet when they require medical information. People seek this information using both traditional search engines and via social media. The information created using the search process offers an unprecedented opportunity for applications to monitor and improve the quality of life of people with a variety of medical conditions. In recent years, research in this area has addressed public-health questions such as the effect of media on development of anorexia, developed tools for measuring influenza rates and assessing drug safety, and examined the effects of health information on individual wellbeing. This tutorial will show how Internet data can facilitate medical research, providing an overview of the state-of-the-art in this area. During the tutorial we will discuss the information which can be gleaned from a variety of Internet data sources, including social media, search engines, and specialized medical websites. We will provide an overview of analysis methods used in recent literature, and show how results can be evaluated using publicly available health information and online experimentation. Finally, we will discuss ethical and privacy issues and possible technological solutions. This tutorial is intended for researchers of user generated content who are interested in applying their knowledge to improve health and medicine.
Original language | English |
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Title of host publication | Proceedings of the 8th ACM International Conference on Web Search and Data Mining |
Number of pages | 2 |
Publisher | Association for Computing Machinery |
Publication date | 2015 |
Pages | 417-418 |
ISBN (Print) | 978-1-4503-3317-7 |
DOIs | |
Publication status | Published - 2015 |
Event | ACM International Conference on Web Search and Data Mining - Shanghai, China Duration: 31 Jan 2015 → 6 Feb 2015 Conference number: 8 |
Conference
Conference | ACM International Conference on Web Search and Data Mining |
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Number | 8 |
Country/Territory | China |
City | Shanghai |
Period | 31/01/2015 → 06/02/2015 |
Keywords
- Information retrieval
- Machine learning
- Medicine
- User generated data