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Social Media

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Identifying self-disclosed anxiety on Twitter: A natural language processing approach.

Psychiatry research
BACKGROUND: Text analyses of social media posts are a promising source of mental health information. This study used natural language processing to explore distinct language patterns on Twitter related to self-reported anxiety diagnosis.

Content framing role on public sentiment formation for pre-crisis detection on sensitive issue via sentiment analysis and content analysis.

PloS one
Social media has been tremendously used worldwide for a variety of purposes. Therefore, engagement activities such as comments have attracted many scholars due its ability to reveal many critical findings, such as the role of users' sentiment. Howeve...

Identifying Potential Lyme Disease Cases Using Self-Reported Worldwide Tweets: Deep Learning Modeling Approach Enhanced With Sentimental Words Through Emojis.

Journal of medical Internet research
BACKGROUND: Lyme disease is among the most reported tick-borne diseases worldwide, making it a major ongoing public health concern. An effective Lyme disease case reporting system depends on timely diagnosis and reporting by health care professionals...

Quantum computing and machine learning for Arabic language sentiment classification in social media.

Scientific reports
With the increasing amount of digital data generated by Arabic speakers, the need for effective and efficient document classification techniques is more important than ever. In recent years, both quantum computing and machine learning have shown grea...

Sentiment Analysis of Tweets on Menu Labeling Regulations in the US.

Nutrients
Menu labeling regulations in the United States mandate chain restaurants to display calorie information for standard menu items, intending to facilitate healthy dietary choices and address obesity concerns. For this study, we utilized machine learnin...

Social Listening for Product Design Requirement Analysis and Segmentation: A Graph Analysis Approach with User Comments Mining.

Big data
This study investigates customers' product design requirements through online comments from social media, and quickly translates these needs into product design specifications. First, the exponential discriminative snowball sampling method was propos...

A visual-language foundation model for pathology image analysis using medical Twitter.

Nature medicine
The lack of annotated publicly available medical images is a major barrier for computational research and education innovations. At the same time, many de-identified images and much knowledge are shared by clinicians on public forums such as medical ...

Deep learning for COVID-19 topic modelling via Twitter: Alpha, Delta and Omicron.

PloS one
Topic modelling with innovative deep learning methods has gained interest for a wide range of applications that includes COVID-19. It can provide, psychological, social and cultural insights for understanding human behaviour in extreme events such as...

Hybrid Recommender System for Mental Illness Detection in Social Media Using Deep Learning Techniques.

Computational intelligence and neuroscience
Recommender systems are chiefly renowned for their applicability in e-commerce sites and social media. For system optimization, this work introduces a method of behaviour pattern mining to analyze the person's mental stability. With the utilization o...

On the use of aspect-based sentiment analysis of Twitter data to explore the experiences of African Americans during COVID-19.

Scientific reports
According to data from the U.S. Center for Disease Control and Prevention, as of June 2020, a significant number of African Americans had been infected with the coronavirus disease, experiencing disproportionately higher death rates compared to other...