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Showing 16 of 16 academic articles

Analyzing the Spatiotemporal Patterns in Green Spaces for Urban Studies Using Location-Based Social Media Data

Hidayat Ullah, Wanggen Wan, Saqib Ali Haidery, Naimat Ullah Khan et al. • ISPRS International Journal of Geo-Information (2019)

Green parks are vital public spaces and play a major role in urban living and well-being. Research on the attractiveness of green parks often relies on traditional techniques, such as questionnaires and in-situ surveys, but these methods a...

DOAJ Open Access (DOAJ) DOI: 10.3390/ijgi8110506

Accessibility Assessment of Buildings Based on Multi-Source Spatial Data: Taking Wuhan as a Case Study

Xue Yang, Yanjia Cao, Anqi Wu, Mingqiang Guo et al. • ISPRS International Journal of Geo-Information (2021)

The question of whether each building of housing estate has equal access to nearby social service resources (e.g., public transportation service, catering, entertainment, etc.) is a major concern of citizens. This paper takes Wuhan as a cas...

DOAJ Open Access (DOAJ) DOI: 10.3390/ijgi10100701

Assessing perception and equity of cultural ecosystem services in urban parks using social media data

Yu Zhang, Lin Zhao, Shiyuan Hu • Scientific Reports (2025)

Abstract Scientific assessment of cultural ecosystem services (CESs) levels in urban parks and refined analysis of their spatial equity are essential for residents’ social well-being. However, traditional assessment methods often fail to ca...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-18288-0

Natural language processing in Alzheimer's disease research: Systematic review of methods, data, and efficacy

Arezo Shakeri, Mina Farmanbar • Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring (2025)

Abstract INTRODUCTION Alzheimer's disease (AD) prevalence is increasing, with no current cure. Natural language processing (NLP) offers the potential for non‐invasive diagnostics, social burden assessment, and research advancements in AD. M...

DOAJ Open Access (DOAJ) DOI: 10.1002/dad2.70082

Natural Language Processing of Social Media as Screening for Suicide Risk

Glen Coppersmith, Ryan Leary, Patrick Crutchley, Alex B. Fine • Biomedical Informatics Insights (2018)

Suicide is among the 10 most common causes of death, as assessed by the World Health Organization. For every death by suicide, an estimated 138 people's lives are meaningfully affected, and almost any other statistic around suicide deaths i...

OPENALEX cc-by-nc DOI: https://doi.org/10.1177/1178222618792860 PMC: 6111391

Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts vs. Comment Pools in Three Languages

Ivan S. Blekanov, Nikita Tarasov, Svetlana S. Bodrunova • Future Internet (2022)

Abstractive summarization is a technique that allows for extracting condensed meanings from long texts, with a variety of potential practical applications. Nonetheless, today’s abstractive summarization research is limited to testing the mo...

DOAJ Open Access (DOAJ) DOI: 10.3390/fi14030069

Human Behavior Analysis: A Comprehensive Survey on Techniques, Applications, Challenges, and Future Directions

Siham Essahraui, Ismail Lamaakal, Yassine Maleh, Khalid El Makkaoui et al. • IEEE Access (2025)

Human Behavior Analysis (HBA) has emerged as a critical interdisciplinary field, combining psychology, sociology, artificial intelligence, and data science to model, understand, and predict human behavior across diverse domains. This paper ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3589938

Research on Landscape Perception and Visual Attributes Based on Social Media Data—A Case Study on Wuhan University

Xia Zhang, Danning Xu, Ni Zhang • Applied Sciences (2022)

With the rapid rise of social media, the photo-taking behavior of tourists and their uploaded photos provide a new perspective to explore landscape visual characters. In this study, we provide methodological advancements for assessing lands...

DOAJ Open Access (DOAJ) DOI: 10.3390/app12168346

Siamese text classification network (SiamTCN) for multi-class multi-label information extraction of typhoon disasters from social media data

Zhi He, Chengle Zhou, Liwei Zou, Suhong Zhou et al. • International Journal of Digital Earth (2025)

Accurately monitoring disaster effects is a crucial task in relief efforts (e.g. typhoon rescue). Social media data plays a vital role in disaster management, while deep learning-based methods gain more attention in typhoon disaster researc...

DOAJ Open Access (DOAJ) DOI: 10.1080/17538947.2025.2517790

Python Machine Learning

Sebastian Raschka (2015)

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsAbout This BookLeverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effect...

OPENALEX

A machine learning approach predicts future risk to suicidal ideation from social media data

Arunima Roy, Katerina Nikolitch, Rachel McGinn, Safiya Jinah et al. • npj Digital Medicine (2020)

Abstract Machine learning analysis of social media data represents a promising way to capture longitudinal environmental influences contributing to individual risk for suicidal thoughts and behaviors. Our objective was to generate an algori...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41746-020-0287-6