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Social Media

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FIR: An Effective Scheme for Extracting Useful Metadata from Social Media.

Journal of medical systems
Recently, the use of social media for health information exchange is expanding among patients, physicians, and other health care professionals. In medical areas, social media allows non-experts to access, interpret, and generate medical information f...

Assessing Electronic Cigarette-Related Tweets for Sentiment and Content Using Supervised Machine Learning.

Journal of medical Internet research
BACKGROUND: Electronic cigarettes (e-cigarettes) continue to be a growing topic among social media users, especially on Twitter. The ability to analyze conversations about e-cigarettes in real-time can provide important insight into trends in the pub...

Exploring Spanish health social media for detecting drug effects.

BMC medical informatics and decision making
BACKGROUND: Adverse Drug reactions (ADR) cause a high number of deaths among hospitalized patients in developed countries. Major drug agencies have devoted a great interest in the early detection of ADRs due to their high incidence and increasing hea...

Fast Distributed Dynamics of Semantic Networks via Social Media.

Computational intelligence and neuroscience
We investigate the dynamics of semantic organization using social media, a collective expression of human thought. We propose a novel, time-dependent semantic similarity measure (TSS), based on the social network Twitter. We show that TSS is consiste...

A global optimization approach to multi-polarity sentiment analysis.

PloS one
Following the rapid development of social media, sentiment analysis has become an important social media mining technique. The performance of automatic sentiment analysis primarily depends on feature selection and sentiment classification. While info...

Using support vector machine ensembles for target audience classification on Twitter.

PloS one
The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential customers. In this paper, our aim is to investigate the use of both unsupervised and supervised learning...

Screening Internet forum participants for depression symptoms by assembling and enhancing multiple NLP methods.

Computer methods and programs in biomedicine
Depression is a disease that can dramatically lower quality of life. Symptoms of depression can range from temporary sadness to suicide. Embarrassment, shyness, and the stigma of depression are some of the factors preventing people from getting help ...

Multi-scale compositionality: identifying the compositional structures of social dynamics using deep learning.

PloS one
OBJECTIVE: Social media exhibit rich yet distinct temporal dynamics which cover a wide range of different scales. In order to study this complex dynamics, two fundamental questions revolve around (1) the signatures of social dynamics at different tim...

Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Social media is becoming increasingly popular as a platform for sharing personal health-related information. This information can be utilized for public health monitoring tasks, particularly for pharmacovigilance, via the use of natural la...

AI for Tobacco Control: Identifying Tobacco-Promoting Social Media Content Using Large Language Models.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
INTRODUCTION: Tobacco companies use social media to bypass marketing restrictions. Studies show that exposure to tobacco promotion on social media influences subsequent smoking behavior, yet it is challenging to monitor such content. We developed an ...