Abstract: Traditional manual methods can no longer meet the needs of analyzing the increasing number of literary works, and most existing sentiment analysis technologies are limited to simple ...

Pooled effect sizes (r) were calculated using random-effects meta-analysis with Hartung-Knapp-Sidik-Jonkman correction, and subgroup and meta-regression analyses were conducted to explore potential ...

Background: Depression affects more than 350 million people globally. Traditional diagnostic methods have limitations. Analyzing textual data from social media provides new insights into predicting ...

Two complementary approaches were employed: Study 1 analyzed 1,902 Weibo posts containing “diet” and “social” keywords through latent Dirichlet allocation topic modeling and semantic network analysis ...

Structure content for AI search so it’s easy for LLMs to cite. Use clarity, formatting, and hierarchy to improve your visibility in AI results. In the SEO world, when we talk about how to structure ...

Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral and ...

Abstract: Emotion classification in social media texts has several challenges, such as the characteristics of social media texts that tend to use informal language, unbalanced data distribution, ...

ABSTRACT: This review focuses on the recent advancements in neuroimaging enabled by deep learning techniques, specifically highlighting their applications in brain disorder detection and diagnosis.