AIMC Topic: Social Media

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Serendipity-A Machine-Learning Application for Mining Serendipitous Drug Usage From Social Media.

IEEE transactions on nanobioscience
Serendipitous drug usage refers to the unexpected relief of comorbid diseases or symptoms when taking medication for a different known indication. Historically, serendipity has contributed significantly to identifying many new drug indications. If pa...

Extracting health-related causality from twitter messages using natural language processing.

BMC medical informatics and decision making
BACKGROUND: Twitter messages (tweets) contain various types of topics in our daily life, which include health-related topics. Analysis of health-related tweets would help us understand health conditions and concerns encountered in our daily lives. In...

Formation Generation for Multiple Unmanned Vehicles Using Multi-Agent Hybrid Social Cognitive Optimization Based on the Internet of Things.

Sensors (Basel, Switzerland)
Multi-agent hybrid social cognitive optimization (MAHSCO) based on the Internet of Things (IoT) is suggested to solve the problem of the generation of formations of unmanned vehicles. Through the analysis of the unmanned vehicle formation problem, fo...

A scalable machine learning approach for measuring violent and peaceful forms of political protest participation with social media data.

PloS one
In this paper, we introduce a scalable machine learning approach accompanied by open-source software for identifying violent and peaceful forms of political protest participation using social media data. While violent political protests are statistic...

Keeping it 100: Social Media and Self-Presentation in College Football Recruiting.

Big data
Social media provides a platform for individuals to craft personal brands and influence their perception by others, including potential employers. Yet there remains a need for more research investigating the relationship between individuals' online i...

Detecting Hypoglycemia Incidents Reported in Patients' Secure Messages: Using Cost-Sensitive Learning and Oversampling to Reduce Data Imbalance.

Journal of medical Internet research
BACKGROUND: Improper dosing of medications such as insulin can cause hypoglycemic episodes, which may lead to severe morbidity or even death. Although secure messaging was designed for exchanging nonurgent messages, patients sometimes report hypoglyc...

Tweet Classification Toward Twitter-Based Disease Surveillance: New Data, Methods, and Evaluations.

Journal of medical Internet research
BACKGROUND: The amount of medical and clinical-related information on the Web is increasing. Among the different types of information available, social media-based data obtained directly from people are particularly valuable and are attracting signif...

Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions.

Science and engineering ethics
Artificial intelligence (AI) research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI t...

Effect of incremental feature enrichment on healthcare text classification system: A machine learning paradigm.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Healthcare tweets are particularly challenging due to its sparse layout and its limited character size. Compared to previous method based on "bag of words" (BOW) model, this study uniquely identifies the enrichment protocol ...

Using deep-learning algorithms to derive basic characteristics of social media users: The Brexit campaign as a case study.

PloS one
A recurrent criticism concerning the use of online social media data in political science research is the lack of demographic information about social media users. By employing a face-recognition algorithm to the profile pictures of Facebook users, t...