Social Media-based Platforms Research Articles

Membangun Platform Digital Desa Margamulya Tanjung Kait Untuk Menuju Masyarakat Society 5.0

The village of Margamulya Tj. Kait is one of the foster villages of LPPM Ukrida. From the results of interviews and direct observations, there are several main issues faced by partners, including: limited access and dissemination of financial information and village profiles to external parties as well as to the villagers themselves. Community service is conducted by utilizing technology to develop a digital village community ecosystem where social media-based platforms serve as everyday communication, socialization, and collaboration tools. The implementation method is carried out through: (1) development of social media platforms; (2) training on platform usage. With the developed social media platform program, the target output is achieved through the evaluation of activities, where the benefit of interaction between village officials and villagers, as well as the dissemination and access to important information, becomes easier. Keywords: digital platform; village digitalization; digital village; margamulya village

The development and evaluation of a social media-based HIV knowledge dissemination platform in China

ObjectiveThis study aimed to introduce the development of a social media-based HIV knowledge dissemination platform and evaluate its dissemination effects, users’ feedback, and preferences. MethodsA social media-based HIV knowledge dissemination platform (“Lihui Space”) was developed as a WeChat Official Account (WOA) to disseminate HIV-related information and knowledge to the public and answer subscribers’ questions. A cross-sectional study was conducted on 784 platform subscribers between July 2021 and September 2021 to evaluate users’ experiences with and preferences for the platform. This platform included three content levels about HIV-related information and knowledge: individual level (health self-management), community level (social function), and society level (news and policy), and dissemination information through texts, pictures, videos, and websites. A descriptive analysis was conducted to estimate the dissemination effects of the platform and evaluation scores. ResultsAs of September 16, 2021, this platform’s WeChat Communication Index (WCI) score was 923.60, the total number of users was 100,008, and the total views in one month was more than 724,000. Participants reported a high level of satisfaction with this platform in terms of overall evaluation (23.36 ± 3.06), readability (18.46 ± 2.63), function evaluation (13.93 ± 1.92), design and structure (22.96 ± 3.36), and interactivity (12.56 ± 2.69). ConclusionThis social media-based platform is currently available in the WeChat application. It is a promising tool for HIV knowledge dissemination and addressing disparities in accessing health care resources.

Power of pedaling: Physician well-being as a collaborative effort in social media-based cycling

Background The impact of the COVID-19 pandemic on the lives of radiation oncologists, from the attending to trainee level, has been multifactorial. One such notable shift has been the limitation of colleague interactions to Zoom-type calls for over two years. Moreover, work-related stress has significantly risen largely due to additional and increasingly complex patient management secondary to COVID-related precautions. As part of the run-up to the ACRO 2022 Annual Meeting, we initiated a friendly competition utilizing a social media-based cycling platform to promote physician well-being as part of #TOURdeACRO. The goal was to support both formation of new connections and strengthening of existing ones between colleagues. Methods Team members were solicited via email, social media, the ACRO websites, and word of mouth. #TOURdeACRO occurred between 1/1/2022 and 2/28/2022. Team members competed based on the number of miles they completed using a social media-based cycling platform. Participants were asked to post their rides on social media platforms so that other Team Members could view the rides and offer positive encouragement. Interval updates were given to encourage friendly competition and reinforce continued investment of teammates in one another's progress. At the Annual meeting, all Team Members were given an official ACRO Racing Jersey to strengthen the unified team culture. Results A total of 7 female and 5 male team members participated, including3 resident physicians and 9 attending physicians. Female riders were significantly more productive than male riders, as evident by total combined mileage. The overall winner was determined on the last day of the #TOURdeACRO. The top three productive team members produced 1066 miles, 834 miles, and 787 miles over the two months. Eight riders reported significant increases in weekly and monthly mileage over their baseline in preceding months. Discussion A social media-based cycling platform was useful and effective in creating and fostering a team culture for a demographically diverse group of radiation oncology physicians. Moving forward, additional riders will be recruited and other social media-based platforms that involve exercise (other than cycling) will be explored to further strengthen this inclusive team environment to enhance physician well-being. The impact of the COVID-19 pandemic on the lives of radiation oncologists, from the attending to trainee level, has been multifactorial. One such notable shift has been the limitation of colleague interactions to Zoom-type calls for over two years. Moreover, work-related stress has significantly risen largely due to additional and increasingly complex patient management secondary to COVID-related precautions. As part of the run-up to the ACRO 2022 Annual Meeting, we initiated a friendly competition utilizing a social media-based cycling platform to promote physician well-being as part of #TOURdeACRO. The goal was to support both formation of new connections and strengthening of existing ones between colleagues. Team members were solicited via email, social media, the ACRO websites, and word of mouth. #TOURdeACRO occurred between 1/1/2022 and 2/28/2022. Team members competed based on the number of miles they completed using a social media-based cycling platform. Participants were asked to post their rides on social media platforms so that other Team Members could view the rides and offer positive encouragement. Interval updates were given to encourage friendly competition and reinforce continued investment of teammates in one another's progress. At the Annual meeting, all Team Members were given an official ACRO Racing Jersey to strengthen the unified team culture. A total of 7 female and 5 male team members participated, including3 resident physicians and 9 attending physicians. Female riders were significantly more productive than male riders, as evident by total combined mileage. The overall winner was determined on the last day of the #TOURdeACRO. The top three productive team members produced 1066 miles, 834 miles, and 787 miles over the two months. Eight riders reported significant increases in weekly and monthly mileage over their baseline in preceding months. A social media-based cycling platform was useful and effective in creating and fostering a team culture for a demographically diverse group of radiation oncology physicians. Moving forward, additional riders will be recruited and other social media-based platforms that involve exercise (other than cycling) will be explored to further strengthen this inclusive team environment to enhance physician well-being.

Tackling healthcare inequities through a social media-based platform to connect solid tumor patients with COVID-19 to clinical trials.

e18560 Background: COVID-19 has contributed to healthcare inequity amongst minorities and lower socioeconomic populations, while complicating present anti-cancer treatment regimens. Due to their immunocompromised status, cancer patients are at an increased risk of severe SARS-CoV-2 infection. While sentiment analysis via SM has seen vast growth among healthcare professional, deeper connection and management has been lacking. Given the higher usage of SM impressions and the increase in healthcare disparities especially at the intersection of oncology and COVID-19, the aim of this study was to develop a platform that can: (1) show that the relationships highlighted within these tweets can be realized in biomolecular interactions—specifically within the interaction between solid tumors and COVID-19; (2) use SM data to connect patients with clinical trials. Methods: To determine this relationship, ontologies, which are groupings of terms and related identifiers, such as genes, were created for general search terms, utilizing the Human Phenotype Ontology. They were then combined with “COVID-19” and used as search terms in Twitter’s Standard Search tool. The keywords with the most matches were then queried through clinicaltrials.gov and European Bioinformatics Institute’s (EBI) Protein Search Tool to find relevant clinical trials and proteins. Finally, the proteins found by the EBI protein search were run through the SwissModel Tool to find relevant protein structures before being used in binding using Polar+’s Binding Platform from Iff Technologies, which provides K values related to 50% inhibition for each medication or immunotherapy. This produced a set of disease-specific keywords that are related to top tweets, clinical trials, protein structures, and binding concentration values in relevant biomolecular pathways for the keyword set “Tumor COVID-19”. Results: The example shown in Table is produced via our platform, with keywords with tweet numbers greater than 95% of all tweets with connected keywords used. Conclusions: By utilizing SM with highly relevant keywords, this platform can combat healthcare inequity by connecting patients and their tweets to clinical trials and enhance literacy about their medical conditions, while providing a greater understanding of the biomolecular pathways involved.[Table: see text]

Mechanisms of the Learning Impact of Teacher-Organized Online Schoolwork Sharing Among Primary School Students

Despite the increasing amount of literature on the educational potential of social media for learning, little is understood about how different functions of social media might affect learning in the K-12 context, the primary school education context in particular. This study examined the effect on learning of a key function of social media—online sharing. It examined how teacher-organized online schoolwork sharing on a social media-based platform, Seesaw, influenced a group of primary school students’ learning. Survey responses from 337 primary school students revealed that students had positive perceptions of the impact of schoolwork sharing on learning. Structural equation modeling analysis of the survey responses revealed that online schoolwork sharing influenced individual student learning primarily through enhanced perceptions of the value of online sharing for learning from peer review, which influenced learners’ efforts in schoolwork. Efforts in schoolwork then positively influenced students’ self-efficacy in learning. The findings suggest that primary school teachers should actively utilize the sharing function of social media to facilitate student learning. The findings also underscore the importance of enhancing peer review and students’ perceptions of its value in order to maximize the learning potential of online schoolwork sharing for primary school students.

Spoiled for Choice? Personalized Recommendation for Healthcare Decisions: A Multi-Armed Bandit Approach with a Dynamic Discrete-Choice Scheme

Social media-based platforms tend to provide much information and numerous options for users, making choice overload a prevalent issue in many online communities. Online healthcare communities (OHCs), which provide users with various healthcare interventions to promote healthy behavior and improve adherence, are no exception. When faced with too many choices, however, individuals may find it difficult to decide which behavior intervention to take, especially when they lack the experience or knowledge to evaluate different options. Consequently, the choice overload issue may negatively affect users’ engagement in health management in OHCs. In this study, we take a design-science perspective to propose a recommendation framework that helps users to select healthcare interventions. Taking into account that users’ health behaviors can be highly dynamic and diverse, we propose a multi-armed bandit (MAB)-driven recommendation framework, which enables us to adaptively learn users’ preference variations while promoting recommendation diversity in the meantime. To better adapt an MAB to the healthcare context, we synthesize two innovative model components based on prominent health theories. The first component is a deep-learning-based feature engineering procedure, which is designed to learn crucial recommendation contexts in regard to users’ sequential health histories, health-management experiences, preferences, and intrinsic attributes of healthcare interventions. The second component is a diversity constraint, which structurally diversifies recommendations in different dimensions to provide well-rounded support for individuals’ health management. We apply our approach to an online weight management context and evaluate it rigorously through a series of experiments. Our results demonstrate that each of the design components is effective and that our recommendation design outperforms a wide range of state-of-the-art recommendation systems. Our study contributes to the emerging IS research on the application of business intelligence. The results have important implications for multiple stakeholders, including online healthcare platforms, policymakers, and users.

Towards A Social Media-Based Framework for Disaster Communication

During disasters, social media platforms such as Twitter, Facebook, and YouTube are widely used by people to share information, opinions, experience, and request for urgent needs. These platforms provide tremendous opportunities to detect disaster situations and give insight into their severity. Since disaster happens suddenly, people face a significant challenge to find credible information and take suitable reactions. The focus here is to reach the affected persons with personalized recommendations to prevent them and save their lives. In this paper, we propose a framework of a social media-based platform that aims to detect emergent disaster and improve communication with citizens before, during and after a disaster by generating personalized recommendations in a timely manner.

One person’s trash is another person’s treasure

Purpose Consumer-to-consumer (C2C) electronic commerce (e-commerce) is shaping contemporary retailing. Despite the fact that a large amount of C2C e-commerce is conducted in social media-based platforms (e.g. Facebook), it has remained an unexplored area of research, though social media as a commercial platform can result in differing customer value and, thus, has potential for consumer experiences that lie beyond the reach of traditional C2C e-commerce actors. Consequently, the purpose of this paper is to identify and explore distinct consumer profiles of C2C e-commerce in social media. Design/methodology/approach Confirmatory factor analysis and cluster analysis are employed to analyze the data from a quantitative survey focusing on C2C e-commerce. Findings Four distinct consumer profiles are introduced and discussed: enthusiasts, bargain hunters, salvagers and apathetics. These profiles capture what kind of value consumers perceive in exchanging used goods with other consumers in Facebook. Research limitations/implications The data were collected from one country. Cultural differences in how C2C e-commerce and the role of Facebook are perceived might influence the generalizability of the results. The data set was cross-sectional and based on self-reported data. Practical implications First, the study indicates that the social media can offer a unique platform for C2C e-commerce that may result in unique and differentiated consumption experiences. Second, firms should carefully analyze how their existing segments match the consumer profiles presented in this study (enthusiasts, bargain hunters, salvagers, apathetics) to assess future value creation potential and challenges. Third, traditional retailers should evaluate the possibility of acting as a platform for C2C commerce or other types of C2C interaction in order to offer their customers benefits that are characteristic for C2C e-commerce. Originality/value This study is among the first attempts to profile C2C e-commerce consumers in social media setting. Interestingly, the profiles differ not in terms of traditional consumer demographics, but on the basis of what kind of value they perceive. Altogether, they grant interesting empirical access to explore the potential and implications of social media-based C2C e-commerce.

Population Size Estimation of Gay and Bisexual Men and Other Men Who Have Sex With Men Using Social Media-Based Platforms.

BackgroundGay, bisexual, and other cisgender men who have sex with men (GBMSM) are disproportionately affected by the HIV pandemic. Traditionally, GBMSM have been deemed less relevant in HIV epidemics in low- and middle-income settings where HIV epidemics are more generalized. This is due (in part) to how important population size estimates regarding the number of individuals who identify as GBMSM are to informing the development and monitoring of HIV prevention, treatment, and care programs and coverage. However, pervasive stigma and criminalization of same-sex practices and relationships provide a challenging environment for population enumeration, and these factors have been associated with implausibly low or absent size estimates of GBMSM, thereby limiting knowledge about the dynamics of HIV transmission and the implementation of programs addressing GBMSM.ObjectiveThis study leverages estimates of the number of members of a social app geared towards gay men (Hornet) and members of Facebook using self-reported relationship interests in men, men and women, and those with at least one reported same-sex interest. Results were categorized by country of residence to validate official size estimates of GBMSM in 13 countries across five continents.MethodsData were collected through the Hornet Gay Social Network and by using an a priori determined framework to estimate the numbers of Facebook members with interests associated with GBMSM in South Africa, Ghana, Nigeria, Senegal, Côte d'Ivoire, Mauritania, The Gambia, Lebanon, Thailand, Malaysia, Brazil, Ukraine, and the United States. These estimates were compared with the most recent Joint United Nations Programme on HIV/AIDS (UNAIDS) and national estimates across 143 countries.ResultsThe estimates that leveraged social media apps for the number of GBMSM across countries are consistently far higher than official UNAIDS estimates. Using Facebook, it is also feasible to assess the numbers of GBMSM aged 13-17 years, which demonstrate similar proportions to those of older men. There is greater consistency in Facebook estimates of GBMSM compared to UNAIDS-reported estimates across countries.ConclusionsThe ability to use social media for epidemiologic and HIV prevention, treatment, and care needs continues to improve. Here, a method leveraging different categories of same-sex interests on Facebook, combined with a specific gay-oriented app (Hornet), demonstrated significantly higher estimates than those officially reported. While there are biases in this approach, these data reinforce the need for multiple methods to be used to count the number of GBMSM (especially in more stigmatizing settings) to better inform mathematical models and the scale of HIV program coverage. Moreover, these estimates can inform programs for those aged 13-17 years; a group for which HIV incidence is the highest and HIV prevention program coverage, including the availability of pre-exposure prophylaxis (PrEP), is lowest. Taken together, these results highlight the potential for social media to provide comparable estimates of the number of GBMSM across a large range of countries, including some with no reported estimates.

Artificial Intelligence-Assisted Online Social Therapy for Youth Mental Health.

Introduction: Benefits from mental health early interventions may not be sustained over time, and longer-term intervention programs may be required to maintain early clinical gains. However, due to the high intensity of face-to-face early intervention treatments, this may not be feasible. Adjunctive internet-based interventions specifically designed for youth may provide a cost-effective and engaging alternative to prevent loss of intervention benefits. However, until now online interventions have relied on human moderators to deliver therapeutic content. More sophisticated models responsive to user data are critical to inform tailored online therapy. Thus, integration of user experience with a sophisticated and cutting-edge technology to deliver content is necessary to redefine online interventions in youth mental health. This paper discusses the development of the moderated online social therapy (MOST) web application, which provides an interactive social media-based platform for recovery in mental health. We provide an overview of the system's main features and discus our current work regarding the incorporation of advanced computational and artificial intelligence methods to enhance user engagement and improve the discovery and delivery of therapy content.Methods: Our case study is the ongoing Horyzons site (5-year randomized controlled trial for youth recovering from early psychosis), which is powered by MOST. We outline the motivation underlying the project and the web application's foundational features and interface. We discuss system innovations, including the incorporation of pertinent usage patterns as well as identifying certain limitations of the system. This leads to our current motivations and focus on using computational and artificial intelligence methods to enhance user engagement, and to further improve the system with novel mechanisms for the delivery of therapy content to users. In particular, we cover our usage of natural language analysis and chatbot technologies as strategies to tailor interventions and scale up the system.Conclusions: To date, the innovative MOST system has demonstrated viability in a series of clinical research trials. Given the data-driven opportunities afforded by the software system, observed usage patterns, and the aim to deploy it on a greater scale, an important next step in its evolution is the incorporation of advanced and automated content delivery mechanisms.