Parenting Information on Social Media: Systematic Literature Review.

Background: Social media has become extremely popular among parents to seek parenting information. Despite the increasing academic attention to the topic, studies are scattered across various disciplines. Therefore, this study broadens the scope of the existing reviews by transcending narrow academic subdomains and including all relevant research insights related to parents' information seeking on social media and its consequent effects.

An exploratory qualitative analysis of public awareness, communication dynamics, and behavioral patterns regarding food safety in Mainland China.

Background: Food safety stands as a critical public health concern in China. People's perceptions and communication regarding food safety crises significantly impact their emotions and food preferences. The rise of social media has also complicated information sharing and decision-making.

Accessing the Impact of TikTok's Algorithm on Regional Inequality in Health Information.

This study aims to audit the potential algorithmic bias in TikTok's health-related video recommendation toward geographically diverse groups in China. We employed 120 cloud phones and conducted two agent-based testing experiments simulating users' geographical locations and online behaviors. The results indicated significant regional inequality in video sources recommended by the TikTok algorithm, (118) = 3.

Psychometric properties of the Chinese version of the Need for Privacy Scale.

Introduction: The need for privacy is a high-order psychological need of human, which is closely related to human mental health problems in the digital age. The Need for Privacy Scale (NFP-S) is a reliable measure of need for privacy. This study tested its psychometric characteristics among Chinese populations.

Bottom-up actions: Examining perceived influence of pandemic news, information relevance, perceived media credibility, and pro-community participation.

Objective: When hyper-infectious diseases sweep over the world, pro-community participation has been found to effectively curb the spread of viruses. This study explores the associations among media-related perceptions and media users' pro-community participation during the peak of the 2022 COVID-19 outbreaks in China.

Methods: A cross-sectional survey was conducted among 976 Chinese media users in April 2022 to collect data on their pro-community participation and perceptions of pandemic news influence, information relevance, and credibility of traditional media and social media.

Distal and proximal factors of wearable users' quantified-self dependence: A cognitive-behavioral model.

Objective: While using self-tracking devices for physical health has become ubiquitous, the potential for quantified-self (QS) dependence as a detrimental outcome for mental health is under-explored. This study examined the mechanism of wearable users' QS dependence by investigating both the distal and proximal factors based on a cognitive-behavioral model.

Methods: A total of 535 wearable users aged 18-35 years were surveyed in this study.

Esports buffs: the perceived role of fans and fandoms in U.S. collegiate programs.

Introduction: Collegiate esports-organized competitive gaming-has expanded rapidly in the United States, drawing in student players, broadcasters, and support staff, as well as university employees. Universities have invested financially in esports, hoping to capitalize on gaming fandom to attract prospective students and enhance campus community integration. Little research, however, addresses collegiate esports fandom in depth.

Debates over the role of Traditional Chinese Medicine on COVID-19: A computational comparison between professionals and laypersons in Chinese online knowledge community.

Leveraging a large collection of textual data (N = 21,539) from a Chinese online community, we employed structural topic modeling to investigate the thematic disparities between professionals and laypersons, regarding the effectiveness of Traditional Chinese Medicine (TCM) on COVID-19. Findings reveal that laypersons are the dominant communicators in terms of discussion volume, who often focus on relevant news events, societal or political aspects of TCM. In contrast, professionals keep concentrating on issues related to medical expertise, and do not shift attentions as frequent as laypersons.

A Competition for the Diagnosis of Myopic Maculopathy by Artificial Intelligence Algorithms.

Importance: Myopic maculopathy (MM) is a major cause of vision impairment globally. Artificial intelligence (AI) and deep learning (DL) algorithms for detecting MM from fundus images could potentially improve diagnosis and assist screening in a variety of health care settings.

Objectives: To evaluate DL algorithms for MM classification and segmentation and compare their performance with that of ophthalmologists.

Searching for Love and Babies: A Qualitative Study on Online Social Support Among Women with Infertility.

With the popularity of computer-mediated communication, accessing online social support has become more accessible for women confronting infertility, yet the role of such support for Chinese women remains understudied. This study investigates the online social support experiences of Chinese women navigating infertility within the framework of Cutrona and Suhr's social support. Employing netnography and semi-structured interviews alongside thematic analysis, the findings highlight challenges in informational support due to limitations in online information dissemination, with some degree of overlap observed between informational support and network support.

Using Geovisualizations to Educate the Public About Environmental Health Hazards: What Works and Why.

Purpose Of Review: Informing the public about environmental risks to health is crucial for raising awareness around hazards, and promoting actions that minimize exposures. Geographic visualizations-geovisualizations-have become an increasingly common way to disseminate web-based information about environmental hazards, displaying spatial variations in exposures and health outcomes using a map. Unfortunately, ineffective geovisualizations can result in inaccurate inferences about a hazard, leading to misguided actions or policies.

Unveiling the influence of persuasion strategies on cognitive engagement: an ERPs study on attentional search.

Unlabelled: The objective of this study was to explore the impact of different persuasive strategies, as delineated in the Elaboration Likelihood Model (ELM), on attentional processes using event-related potentials (ERPs).

Introduction: This study aimed to investigate how central versus peripheral persuasion methods, delivered through rational and emotional persuasion strategies, influence cognitive engagement and information processing during visual search tasks.

Methods: Participants were allocated into four groups based on the media type (video vs.

Predicting social media users' indirect aggression through pre-trained models.

Indirect aggression has become a prevalent phenomenon that erodes the social media environment. Due to the expense and the difficulty in determining objectively what constitutes indirect aggression, the traditional self-reporting questionnaire is hard to be employed in the current cyber area. In this study, we present a model for predicting indirect aggression online based on pre-trained models.

Multi-modal deep learning framework for damage detection in social media posts.

In crisis management, quickly identifying and helping affected individuals is key, especially when there is limited information about the survivors' conditions. Traditional emergency systems often face issues with reachability and handling large volumes of requests. Social media has become crucial in disaster response, providing important information and aiding in rescues when standard communication systems fail.

Understanding internal dynamics of state anxiety during COVID-19 pandemic: Seven-wave longitudinal findings via panel network analysis.

Research on state anxiety has long been dominated by the traditional psychometric approach that assumes anxiety symptoms have a common cause. Yet state anxiety can be conceptualized as a network system. In this study, we utilized data from the COVID-Dynamic dataset from waves 7 to 13, collected at three-week intervals from June 6, 2020, to October 13, 2020, and included 1,042 valid participants to characterize the internal dynamics of state anxiety.

From personality types to social labels: the impact of using MBTI on social anxiety among Chinese youth.

Introduction: As the Myers-Briggs Type Indicator (MBTI) gains popularity among Chinese young people, it has undergone a gradual transition from being perceived as a personality assessment tool to being regarded as a social label. The objective of this study was to ascertain whether the use of the MBTI as a social label has an impact on social anxiety among Chinese youth groups.

Methods: A questionnaire survey was conducted on social media platforms to recruit Chinese youth aged 18 to 35.

Prediction techniques of movie box office using neural networks and emotional mining.

Box office prediction is of great significance for understanding investment risks, class construction, promotion and distribution, and theater scheduling. However, due to the insufficient selection of influencing factors of movie box office, the currently existing prediction model restricts the prediction accuracy. A total of 34 influencing factors in 11 categories, such as heat index, movie types, release date, creators, first-day box office, were selected to study the prediction technology of movie box office.

The impact of attitude toward COVID-19 vaccine on intention to receive influenza vaccination: a multi-group comparison based on the influence of presumed influence model and spillover effects.

Introduction: Influenza vaccination is one of the most important strategies for preventing influenza. However, the influenza vaccination rate in China remains low. During the COVID-19 pandemic, people held different attitudes toward the COVID-19 vaccine.