Lin Luo^1,2,*, Junfeng Yuan¹, Yanling Wang¹, Rui Zhu¹, Huilin Xu¹, Siyuan Bi¹, Zhongge Zhang¹

International Journal of Mental Health Promotion, Vol.27, No.6, pp. 863-876, 2025, DOI:10.32604/ijmhp.2025.064385 - 30 June 2025

Abstract Objectives: Social Network Addiction (SNA) is becoming increasingly prevalent among college students; however, there remains a lack of consensus regarding the measurement tools and their optimal cutoff score. This study aims to validate the 21-item Social Network Addiction Scale-Chinese (SNAS-C) in its Chinese version and to determine its optimal cutoff score for identifying potential SNA cases within the college student population. Methods: A cross-sectional survey was conducted, recruiting 3387 college students. Latent profile analysis (LPA) and receiver operating characteristic (ROC) curve analysis were employed to establish the optimal cutoff score for the validated 21-item SNAS-C. Results:… More >

Sangmin Kim¹, Byeongcheon Lee¹, Muazzam Maqsood², Jihoon Moon^3,*, Seungmin Rho^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 2079-2108, 2025, DOI:10.32604/cmes.2025.061653 - 30 May 2025

Abstract The increased accessibility of social networking services (SNSs) has facilitated communication and information sharing among users. However, it has also heightened concerns about digital safety, particularly for children and adolescents who are increasingly exposed to online grooming crimes. Early and accurate identification of grooming conversations is crucial in preventing long-term harm to victims. However, research on grooming detection in South Korea remains limited, as existing models trained primarily on English text and fail to reflect the unique linguistic features of SNS conversations, leading to inaccurate classifications. To address these issues, this study proposes a novel… More >

Xiaowen Wan¹, Wenbin Sheng¹, Rong Huang¹, Cheng Zeng¹, Xu Zhou^2,*, Yuan Wu³, Xiaohui Cao¹, Xiaoke Chen¹

International Journal of Mental Health Promotion, Vol.27, No.2, pp. 215-229, 2025, DOI:10.32604/ijmhp.2025.059074 - 03 March 2025

Abstract Background: As the digital age progresses, fear of missing out (FoMO) is becoming increasingly common, and the impact factor of FOMO needs to be further investigated. This study aims to explore the relationship between psychological security (PS) and FoMO by analyzing the mediating role of social networking addiction (SNA) and the moderating role of social self-efficacy (SSE). Methods: We collected a sample of 1181 college students (with a mean age of 19.67 ± 1.38 years) from five universities in a province of mainland China through cluster sampling. Data were gathered using the psychological security questionnaire… More >

Divya P. Vijayan¹, Tokani Ghuhato¹, Eslavath Rajkumar^2,*, Allen Joshua George³, Romate John¹, John Abraham⁴

International Journal of Mental Health Promotion, Vol.26, No.5, pp. 389-398, 2024, DOI:10.32604/ijmhp.2024.023032 - 30 May 2024

Abstract ‘Selfie’ taking was introduced to the common people by smartphones and has become a common practice across the globe in no time. With technological advancement and the popularity of smartphones, selfie-taking has grown rapidly within a short time. In light of the new trend set by the generation, this study aimed to explore reasons for selfie-taking and selfie-posting on social media and their effects on the social and psychological lives of young adults. A purposive sampling method was adopted to select 20 Indian citizens, between 18 and 24 years. The data were collected through semi-structured More >

Siyuan Bi¹, Junfeng Yuan^1,2, Lin Luo^1,2,3,*

International Journal of Mental Health Promotion, Vol.26, No.1, pp. 51-60, 2024, DOI:10.32604/ijmhp.2023.041614 - 05 February 2024

Abstract Purpose: The core component theory of addiction behavior provides a multidimensional theoretical model for measuring social networking addiction. Based on this theoretical model, the Social Networking Addiction Scale (SNAS) was developed. The aim of this study was to test the psychometric properties of the Chinese version of the SNAS (SNAS-C). Methods: This study used a sample of 3383 Chinese university students to conduct confirmatory factor analysis (CFA) to explore the structural validity of the SNAS-C. This study examined the Pearson correlations between the six subscales of the SNAS-C (i.e., salience, mood modification, tolerance, withdrawal symptoms,… More >

Xiaolin Lu^1,*, Xiaolei Miao²

International Journal of Mental Health Promotion, Vol.25, No.9, pp. 1041-1052, 2023, DOI:10.32604/ijmhp.2023.030232 - 10 August 2023

Abstract Background: During the early stages of the COVID-19 pandemic in China, social interactions shifted to online spaces due to lock-downs and social distancing measures. As a result, the impact of online social networking on users’ emotional status has become stronger than ever. This study examines the association between online social networking and Internet users’ emotional status and how offline reality affects this relationship. Methods: The study utilizes cross-sectional online survey data (n = 3004) and Baidu Migration big data from the first 3 months of the pandemic. Two dimensions of online networking are measured: social… More > Graphic Abstract

Abeer D. Algarni^*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 1233-1247, 2023, DOI:10.32604/csse.2022.026915 - 26 May 2023

Abstract Exponential increase in the quantity of user generated content in websites and social networks have resulted in the emergence of web intelligence approaches. Several natural language processing (NLP) tools are commonly used to examine the large quantity of data generated online. Particularly, sentiment analysis (SA) is an effective way of classifying the data into different classes of user opinions or sentiments. The latest advances in machine learning (ML) and deep learning (DL) approaches offer an intelligent way of analyzing sentiments. In this view, this study introduces a web intelligence with enhanced sunflower optimization based deep… More >

Muhammad Riaz¹, Masooma Raza Hashmi¹, Faruk Karaaslan², Aslıhan Sezgin³, Mohammed M. Ali Al Shamiri^4,5,*, Mohammed M. Khalaf^6,7

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1759-1783, 2023, DOI:10.32604/cmes.2023.023327 - 06 February 2023

Abstract This paper aims to introduce the novel concept of neutrosophic crisp soft set (NCSS), including various types of neutrosophic crisp soft sets (NCSSs) and their fundamental operations. We define NCS-mapping and its inverse NCS-mapping between two NCS-classes. We develop a robust mathematical modeling with the help of NCS-mapping to analyze the emerging trends in social networking systems (SNSs) for our various generations. We investigate the advantages, disadvantages, and natural aspects of SNSs for five generations. With the changing of the generations, it is analyzed that emerging trends and the benefits of SNSs are increasing day More > Graphic Abstract

Hanan Abdullah Mengash¹, Jaber S. Alzahrani², Majdy M. Eltahir³, Fahd N. Al-Wesabi⁴, Abdullah Mohamed⁵, Manar Ahmed Hamza^6,*, Radwa Marzouk⁷

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1393-1407, 2023, DOI:10.32604/csse.2023.030328 - 03 November 2022

Abstract Presently, smart cities play a vital role to enhance the quality of living among human beings in several ways such as online shopping, e-learning, e-healthcare, etc. Despite the benefits of advanced technologies, issues are also existed from the transformation of the physical word into digital word, particularly in online social networks (OSN). Cyberbullying (CB) is a major problem in OSN which needs to be addressed by the use of automated natural language processing (NLP) and machine learning (ML) approaches. This article devises a novel search and rescue optimization with machine learning enabled cybersecurity model for… More >

Swarna Sudha Muppudathi¹, Valarmathi Krishnasamy^2,*

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1027-1042, 2023, DOI:10.32604/iasc.2023.031165 - 29 September 2022

Abstract Social Networking Sites (SNSs) are nowadays utilized by the whole world to share ideas, images, and valuable contents by means of a post to reach a group of users. The use of SNS often inflicts the physical and the mental health of the people. Nowadays, researchers often focus on identifying the illegal behaviors in the SNS to reduce its negative influence. The state-of-art Natural Language processing techniques for anomaly detection have utilized a wide annotated corpus to identify the anomalies and they are often time-consuming as well as certainly do not guarantee maximum accuracy. To overcome… More >