Applications of social media Ch 4 Health care applications Financial

Applications of social media ch 4 health care

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Applications of social media (Ch 4) Health care applications Financial applications Predicting voting intentions Security and defence applications Disaster response applications NLP-based user modelling NLP-based information visualisation for SM Applications for entertainment Media monitoring
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Health care applications Many online platforms where people discuss their health : Specialized forums , for various topics. The language is often informal and medical terms can be found, but most of the language is lay. Various kinds of information can be extracted automatically from such postings and discussions. Opinions and arguments pro and cons topics such as: vaccinations, mammographies, new born genetic screening. Need privacy protection : detection of personal health information (PHI) such as names, dates of birth, addresses, health insurance numbers.
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Health care applications (cont.) SocialMed : detecting early signs of mental heath problems: Can social media be used to detect affective disorderssuch as depressionand other mental health issues? Emotion analysis, unusual emotions User profiling(age, gender, personality) Can we build automatic prediction models to identify at-risk individualsin onlinecommunities? Applicationscenarios? Post monitoring of patients with their consent Monitoringhigh-risk communities / population Suicide prevention (uOttawa project).
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Financial applications Behavioral economics studies the correlation between public mood and economic indicators, and between financial news / rumors and stock exchange fluctuations Recent studies show that using social media (Twitter, Sina weibo, Seeking Alpha) data to automatically measure public mood (rather than using expensive traditional polls) can be useful in financial applications Experiments wererun on predicting stock market fluctuations for NASDAQ, New York Stock Exchange,DOW Jones, S&P 500, ShanghaiStock Exchange,Turkish Stock Exchange,etc.
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Predicting voting intentions Need to detect messages about the desired topic or political entities of interest (using keyword search or text classification methods). Then use opinion detection / sentiment analysis techniques . Experiments: Automatic opinion pollinggiven a comments written after voting, on the SodaHead social polling website. Tjong Kim Sang and Bos (2012) used Twitter data to predict the 2011 Dutch Senate Election Results. Bermingham and Smeaton (2011) used social media for prediction of the 2011 Irish GeneralElection. Severalstudies on US elections using congress debates, political blogs and their comments, Twitter data, etc.
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Disaster response applications A sudden change in the topics discussed in social media in a region can indicate a possible emergency situation , for example a natural disaster such as an earthquake, fire, tsunami, or flooding.
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