AIMC Topic: Social Media

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Mining e-cigarette adverse events in social media using Bi-LSTM recurrent neural network with word embedding representation.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2018
OBJECTIVE: Recent years have seen increased worldwide popularity of e-cigarette use. However, the risks of e-cigarettes are underexamined. Most e-cigarette adverse event studies have achieved low detection rates due to limited subject sample sizes in...
Humans Neural Networks, Computer Semantics Vaping Electronic Nicotine Delivery Systems Social Media Data Mining
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Machine Learning, Sentiment Analysis, and Tweets: An Examination of Alzheimer's Disease Stigma on Twitter.

The journals of gerontology. Series B, Psychological sciences and social sciences Sep 1, 2017
OBJECTIVES: Social scientists need practical methods for harnessing large, publicly available datasets that inform the social context of aging. We describe our development of a semi-automated text coding method and use a content analysis of Alzheimer...
Humans Machine Learning Ageism Social Stigma Public Opinion United States Social Media Data Mining Algorithms Aged Alzheimer Disease Female Aged, 80 and over Disability Evaluation Male
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AI in Action: How algorithms can analyze the mood of the masses.

Science (New York, N.Y.) Jul 7, 2017
Mass Behavior Humans Machine Learning Social Media Affect Algorithms
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Learning about individuals' health from aggregate data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2017
There is growing awareness that user-generated social media content contains valuable health-related information and is more convenient to collect than typical health data. For example, Twitter has been employed to predict aggregate-level outcomes, s...
Social Media Health Records, Personal Machine Learning Algorithms Humans
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Identifying personal health experience tweets with deep neural networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2017
Twitter, as a social media platform, has become an increasingly useful data source for health surveillance studies, and personal health experiences shared on Twitter provide valuable information to the surveillance. Twitter data are known for their i...
Neural Networks, Computer Social Media Internet
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Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2017
OBJECTIVE: Social media is an important pharmacovigilance data source for adverse drug reaction (ADR) identification. Human review of social media data is infeasible due to data quantity, thus natural language processing techniques are necessary. Soc...
Neural Networks, Computer Machine Learning Social Media Humans Pharmacovigilance Natural Language Processing Drug-Related Side Effects and Adverse Reactions
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Artificial intelligence: A social spin on language analysis.

Nature May 10, 2017
Machine Learning Software Support Vector Machine Social Media Language Humans Neural Networks, Computer Bullying Search Engine Data Mining Agonistic Behavior Crowdsourcing Uncertainty Verbal Behavior
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Using life's digital detritus to feed discovery.

The lancet. Psychiatry Mar 1, 2017
Early Diagnosis Mental Health Social Media Machine Learning Humans Psychiatry Risk Factors
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Toward Automating HIV Identification: Machine Learning for Rapid Identification of HIV-Related Social Media Data.

Journal of acquired immune deficiency syndromes (1999) Feb 1, 2017
INTRODUCTION: "Social big data" from technologies such as social media, wearable devices, and online searches continue to grow and can be used as tools for HIV research. Although researchers can uncover patterns and insights associated with HIV trend...
Social Media Statistics as Topic Epidemiologic Methods Humans HIV Infections Time Factors Machine Learning Risk-Taking
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Comparing the Human Papillomavirus Vaccination Opinions Trends from Different Twitter User Groups with a Machine Learning Based System and Semiparametric Nonlinear Regression.

Studies in health technology and informatics Jan 1, 2017
HPV vaccination refusal is a serious public health issue. Opinions on Twitter have are influential to potential consumers on vaccination behaviours. Public opinions toward HPV vaccination were extracted from Twitter by leveraging machine learning mod...
Social Media Attitude Papillomavirus Vaccines Public Opinion Humans Papillomavirus Infections Machine Learning Vaccination
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