Exploring COVID-19–Related Stressors: Topic Modeling Study by Yue Tong Leung, Farzad Khalvati

“…ObjectiveThis study aims to apply natural language processing (NLP) techniques to social media data to identify the psychosocial stressors during the COVID-19 pandemic and to analyze the trend in the prevalence of these stressors at different stages of the pandemic. …”
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Analyzing the function of metaverse technology in the retention and absorption of knowledge using the integrated approach of interpretive structural modeling and structural equatio... by seyed mojtaba Hosseini Bamakan, hajar soleymanizadeh, Mehran Ziaeian

“…The results of this research showed that metaverse technology through capabilities such as environmental artificial intelligence, simulation, natural language processing, use of social networks, data analysis, knowledge organization, cooperation, knowledge sharing. …”
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Word-Level and Pinyin-Level Based Chinese Short Text Classification by Xinjie Sun, Xingying Huo

“…Short text classification is an important branch of Natural Language Processing. Although CNN and RNN have achieved satisfactory results in the text classification tasks, they are difficult to apply to the Chinese short text classification because of the data sparsity and the homophonic typos problems of them. …”
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Developing data governance standards for using free-text data in research (TexGov) by Kerina Jones, Elizabeth Ford, Nathan Lea, Lucy Griffiths, Sharon Heys, Emma Squires

“…The main emerging themes were: i) patient involvement at identifiable and de-identified data stages; ii) questions of consent and notification for the reuse of free-text data; iii) working with identifiable data for Natural Language Processing algorithm development; and iv) de-identification methods and thresholds of reliability. …”
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Feature-enhanced fusion of U-NET-based improved brain tumor images segmentation by Abdul Haseeb Nizamani, Zhigang Chen, Ahsan Ahmed Nizamani, Kashif Shaheed

“…In contrast, the advent of Transformers, which has established their prowess in natural language processing and computer vision, offers a promising alternative. …”
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Exploring the Credibility of Large Language Models for Mental Health Support: Protocol for a Scoping Review by Dipak Gautam, Philipp Kellmeyer

“… BackgroundThe rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are increasingly integrated into various applications, including mental health support. …”
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ProtPlat: an efficient pre-training platform for protein classification based on FastText by Yuan Jin, Yang Yang

“…In recent years, pre-training methods have been widely studied to address the small-sample issue in computer vision and natural language processing fields, while specific pre-training techniques for protein sequences are few. …”
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A New Hybrid Based on Long Short-Term Memory Network with Spotted Hyena Optimization Algorithm for Multi-Label Text Classification by Hamed Khataei Maragheh, Farhad Soleimanian Gharehchopogh, Kambiz Majidzadeh, Amin Babazadeh Sangar

“…An essential work in natural language processing is the Multi-Label Text Classification (MLTC). …”
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Machine learning-based identification and rule-based normalization of adverse drug reactions in drug labels by Mert Tiftikci, Arzucan Özgür, Yongqun He, Junguk Hur

“…Therefore, systematically identifying ADR information from drug labels is critical in multiple aspects; however, this task is challenging due to the nature of the natural language of drug labels. Results In this paper, we present a machine learning- and rule-based system for the identification of ADR entity mentions in the text of drug labels and their normalization through the Medical Dictionary for Regulatory Activities (MedDRA) dictionary. …”
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From Vulnerability to Defense: The Role of Large Language Models in Enhancing Cybersecurity by Wafaa Kasri, Yassine Himeur, Hamzah Ali Alkhazaleh, Saed Tarapiah, Shadi Atalla, Wathiq Mansoor, Hussain Al-Ahmad

“…LLMs, such as GPT, BERT, and PaLM, demonstrate unparalleled capabilities in natural language processing, enabling them to parse vast datasets, identify vulnerabilities, and automate threat detection. …”
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Estimation of Psychological Distress in Japanese Youth Through Narrative Writing: Text-Based Stylometric and Sentiment Analyses by Masae Manabe, Kongmeng Liew, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki

“…Text-based detection using natural language processing (NLP) methods is increasingly being used to complement conventional detection efforts. …”
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SPECIAL ISSUE : "Integrative medicine in oncology: another step forward" - PROSTATE CANCER PATIENTS AND THEIR INTERACTIONS WITH ONLINE ONCOLOGY COMMUNITIES: A MACHINE LEARNING SENT... by Dario Piazza, Nicola Borsellino, Vincenzo Serretta, Vittorio Gebbia

“…We apply to the dataset a sentiment analysis using an unsupervised approach of Natural Language Processing Results Three thousand ve hundred forty-nine messages exchanged by 219 members belonging to the prostate cancer posts were extracted from 2010 to 2019 for 39,040 words. …”
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Identifying False Human Papillomavirus (HPV) Vaccine Information and Corresponding Risk Perceptions From Twitter: Advanced Predictive Models by Tre Tomaszewski, Alex Morales, Ismini Lourentzou, Rachel Caskey, Bing Liu, Alan Schwartz, Jessie Chin

“…MethodsThis study used machine learning and natural language processing to develop a series of classification models and causality mining methods to identify and examine true and false HPV vaccine–related information on Twitter. …”
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The impact of memory on learning sequence-to-sequence tasks by Alireza Seif, Sarah A M Loos, Gennaro Tucci, Édgar Roldán, Sebastian Goldt

“…The recent success of neural networks in natural language processing has drawn renewed attention to learning sequence-to-sequence (seq2seq) tasks. …”
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Thematic Analysis of Indonesian Physics Education Research Literature Using Machine Learning by Purwoko Haryadi Santoso, Edi Istiyono, Haryanto, Wahyu Hidayatulloh

“…In order to deal with this plethora of publications, one of the machine learning (ML) algorithms from natural language processing (NLP) studies was employed in this paper to automate a thematic analysis of Indonesian PER literature that still needs to be explored within the community. …”
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Emotion-Based Sentiment Analysis Using Conv-BiLSTM with Frog Leap Algorithms by Sandeep Yelisetti, Nellore Geethanjali

“…Emotion identification from the text in natural language processing (NLP) provides more benefits in the field of e-commerce and business environments. …”
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Investigating Offensive Language Detection in a Low-Resource Setting with a Robustness Perspective by Israe Abdellaoui, Anass Ibrahimi, Mohamed Amine El Bouni, Asmaa Mourhir, Saad Driouech, Mohamed Aghzal

“…Moroccan Darija, a dialect of Arabic, presents unique challenges for natural language processing due to its lack of standardized orthographies, frequent code switching, and status as a low-resource language. …”
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COMPARATIVE ANALYSIS OF MULTILINGUAL QA MODELS AND THEIR ADAPTATION TO THE KAZAKH LANGUAGE by Arailym Tleubayeva, Aday Shomanov

“…By addressing these challenges, this research aims to make AI technologies more inclusive and accessible, offering practical insights for improving natural language processing (NLP) capabilities in underrepresented languages. …”
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PTG-PLM: Predicting Post-Translational Glycosylation and Glycation Sites Using Protein Language Models and Deep Learning by Alhasan Alkuhlani, Walaa Gad, Mohamed Roushdy, Michael Gr. Voskoglou, Abdel-badeeh M. Salem

“…In recent years, advances in Transformer-based Language Models based on deep learning have been transferred from Natural Language Processing (NLP) into the proteomics field by developing language models for protein sequence representation known as Protein Language Models (PLMs). …”
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Enhancing Disaster Situation Awareness Through Multimodal Social Media Data: Evidence from Typhoon Haikui by Songfeng Gao, Tengfei Yang, Yuning Xu, Naixia Mou, Xiaodong Wang, Hao Huang

“…We employed the ERNIE natural language processing model to complement the Deeplab v3+ deep learning image semantic segmentation model for extracting disaster damage information from social media. …”
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