University of Ottawa - Carleton University
Ottawa-Carleton Institute for Computer Science (OCICS) Presentation
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March 8, 2013 @ 10:00
Text Mining for Patient Opinions in Online Communities
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Speaker: Tanveer Ali
Location: 240 TB (Tory Building) |
ABSTRACT
Development of Internet and user-friendly Web technologies profoundly changed the ways the general public can express their opinions on multitude of topics. It became imperative to incorporate online-posted information into decisions related to public health (Eysenbach, 2009). In order to make educated decisions, there is a necessity to develop methods that adequately â efficiently and effectively â extract a new knowledge from the online messages. Being dependable on individual's personality, culture and expectations of the society, opinions are challenging for independent external evaluation and categorization. Text Mining has investigated relations between positive and negative opinions and patient's physical health. Several studies linked the personal lexicon with health and health behavior of the individual (Pennebaker et al., 2003). Studies of coronary diseases have shown relations between the disease risks and the use of language expressions of self-involvement (Rhodewalt, 1984; Scherwitz & Canick, 1988). However, there were not Text Mining studies performed to analyze opinions expressed in a large volume of user-written Web content.Therefore we want to investigate opinions of people related to stigma of Hearing Loss (HL). consequences of HL surgeries, living with HL, failures of HL loss treatments, etc. on some medical forums. |
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