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Social Media

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Code-mixing unveiled: Enhancing the hate speech detection in Arabic dialect tweets using machine learning models.

PloS one
Technological developments over the past few decades have changed the way people communicate, with platforms like social media and blogs becoming vital channels for international conversation. Even though hate speech is vigorously suppressed on socia...

MGLEP: Multimodal Graph Learning for Modeling Emerging Pandemics with Big Data.

Scientific reports
Accurate forecasting and analysis of emerging pandemics play a crucial role in effective public health management and decision-making. Traditional approaches primarily rely on epidemiological data, overlooking other valuable sources of information th...

Leveraging textual information for social media news categorization and sentiment analysis.

PloS one
The rise of social media has changed how people view connections. Machine Learning (ML)-based sentiment analysis and news categorization help understand emotions and access news. However, most studies focus on complex models requiring heavy resources...

Beyond algorithms: The human touch machine-generated titles for enhancing click-through rates on social media.

PloS one
Artificial intelligence (AI) has the potential to revolutionize various domains by automating language-driven tasks. This study evaluates the effectiveness of an AI-assisted methodology, called the "POP Title AI Five-Step Optimization Method," in opt...

HAPI: An efficient Hybrid Feature Engineering-based Approach for Propaganda Identification in social media.

PloS one
Social media platforms serve as communication tools where users freely share information regardless of its accuracy. Propaganda on these platforms refers to the dissemination of biased or deceptive information aimed at influencing public opinion, enc...

Predicting negative attitudes towards suicide in social media texts: prediction model development and validation study.

Frontiers in public health
BACKGROUND: Implementing machine learning prediction of negative attitudes towards suicide may improve health outcomes. However, in previous studies, varied forms of negative attitudes were not adequately considered, and developed models lacked rigor...

Insights Derived From Text-Based Digital Media, in Relation to Mental Health and Suicide Prevention, Using Data Analysis and Machine Learning: Systematic Review.

JMIR mental health
BACKGROUND: Text-based digital media platforms have revolutionized communication and information sharing, providing valuable access to knowledge and understanding in the fields of mental health and suicide prevention.

Assessing inclusion and representativeness on digital platforms for health education: Evidence from YouTube.

Journal of biomedical informatics
BACKGROUND: Studies confirm that significant biases exist in online recommendation platforms, exacerbating pre-existing disparities and leading to less-than-optimal outcomes for underrepresented demographics. We study issues of bias in inclusion and ...

Using AI-Based Virtual Companions to Assist Adolescents with Autism in Recognizing and Addressing Cyberbullying.

Sensors (Basel, Switzerland)
Social media platforms and online gaming sites play a pervasive role in facilitating peer interaction and social development for adolescents, but they also pose potential threats to health and safety. It is crucial to tackle cyberbullying issues with...

Applying deep learning on social media to investigate cultural ecosystem services in protected areas worldwide.

Scientific reports
Protected areas (PAs) are the cornerstone of conservation efforts. Although they provide many benefits to humanity, the variability in the provision of cultural ecosystem services (CES) among global PAs remains unknown. To investigate this, we combin...