(Learning or education) AND "social network analysis"

With the development of various applications, such as recommendation systems and social network analysis, graph data have been ubiquitous in the real world. However, graphs usually suffer from being absent during data collection due to copyright restrictions or privacy-protecting policies. The graph absence could be roughly grouped into attribute-incomplete and attribute-missing cases. Specifically, attribute-incomplete indicates that a portion of the attribute vectors of all nodes are incomplete, while attribute-missing indicates that all attribute vectors of partial nodes are missing...

PURPOSE: This study aimed to identify the main keyword, network structure, and main topics of the national petition related to "nursing" in South Korea. METHODS: Data were gathered from petitions related to the national petition in Korea Blue House related to the topic "nursing" or "nurse" from August 17, 2017, to May 9, 2022. A total of 5,154 petitions were searched, and 995 were selected for the final analysis. Text network analysis and topic modeling were analyzed using the Netminer 4...

Colorectal cancer (CRC) is a primary global health concern, and identifying the molecular pathways, genetic subtypes, and mutations associated with CRC is crucial for precision medicine. However, traditional measurement techniques such as gene sequencing are costly and time-consuming, while most deep learning methods proposed for this task lack interpretability. This study offers a new approach to enhance the state-of-the-art deep learning methods for molecular pathways and key mutation prediction by incorporating cell network information...

BACKGROUND: One Health focuses on sustainable health for humans, animals, and ecosystems. The approach has been well demonstrated, yet most efforts have not been scaled up. Understanding the organisations involved in scaling up processes is critical to translating research into practice. The Lao People's Democratic Republic has successfully implemented One Health projects for multiple decades; however, the organisational network has not been described and scaling up efforts have been limited...

PURPOSE: Social network analysis (SNA) is a theoretical framework and analytical approach used to study relationships among individuals and groups. While SNA has been employed by many disciplines to understand the social structures and dynamics of interpersonal relationships, little is known about its use in medical education. Mapping and synthesizing the scope of SNA in undergraduate and postgraduate medical education can inform educational practice and research. METHOD: This scoping review was based on searches conducted in Medline, Embase, Scopus, and ERIC in December 2020, and updated in March 2022...

This data article provides a dataset of 132421 posts and their corresponding information collected from Twitter social media. The data has two classes, ham or spam, where ham indicates non-spam clean tweets. The main target of this dataset is to study a way to classify whether a post is a spam or not automatically. The data is in Arabic language only, which makes the data essential to the researchers in Arabic natural language processing (NLP) due to the lack of resources in this language. The data is made publicly available to allow researchers to use it as a benchmark for their research in Arabic NLP...

With the progress and development of computer technology, applying machine learning methods to cancer research has become an important research field. To analyze the most recent research status and trends, main research topics, topic evolutions, research collaborations, and potential directions of this research field, this study conducts a bibliometric analysis on 6206 research articles worldwide collected from PubMed between 2011 and 2021 concerning cancer research using machine learning methods. Python is used as a tool for bibliometric analysis, Gephi is used for social network analysis, and the Latent Dirichlet Allocation model is used for topic modeling...

The cognitive and performance benefits of group work in undergraduate courses depend on understanding how to structure groups to promote communication and comfort while also promoting diversity and reducing conflict. The current study utilized social network analysis combined with self-reported survey data from 555 students in 155 groups to understand how students identified group members whom they wished to work with. Students' willingness to work with their peers was positively associated with behavioral traits pertaining to attention, participation, and preparedness in class...

OBJECTIVE: This paper examines the acceptance of the Advocacy Core Group (ACG) programme, a social and behaviour change intervention addressing maternal, newborn, child health and nutrition (MNCH+N) in Bauchi and Sokoto states, with an additional focus on the perceived endorsement of health behaviours by social networks as a potential factor influencing acceptance. DESIGN: This study used the qualitative social network analysis approach and used in-depth interviews to collect data from 36 participants across Bauchi and Sokoto states...

Over the last decade, there has been a large amount of research on technology-enhanced learning (TEL), including the exploration of sensor-based technologies. This research area has seen significant contributions from various conferences, including the European Conference on Technology-Enhanced Learning (EC-TEL). In this research, we present a comprehensive analysis that aims to identify and understand the evolving topics in the TEL area and their implications in defining the future of education. To achieve this, we use a novel methodology that combines a text-analytics-driven topic analysis and a social network analysis following an open science approach...

No abstract text is available yet for this article.

BACKGROUND: Friendships play a vital role in the social lives of teenagers, and friendship quality can substantially impact the adolescents' overall health and wellbeing. This study aimed to investigate the association between friendship quality and subjective wellbeing in Northern Irish adolescents. METHODS: In this cross-sectional observational study, we used data from the second wave of the Wellbeing in Schools Survey, conducted in Northern Ireland from April 2 to May 31, 2018...

While several studies have investigated gender inequities in the social learning environment of biology lecture courses, that same phenomenon remains largely unexplored in biology laboratory contexts. We conducted a mixed methods study to understand the influence of gender on student perceptions of their peers' research aptitude in introductory biology CUREs and traditional laboratory courses. Specifically, students ( N = 125) were asked to complete a name generator survey at three time points across the semester...

BACKGROUND: Social network interventions are an effective approach to promote physical activity. These interventions are traditionally designed using self-reported peer nomination network data to represent social connections. However, there is unexplored potential in communication data exchanged through web-based messaging apps or social platforms, given the availability of these data, the developments in artificial intelligence to analyze these data, and the shift of personal communication to the web sphere...

Balanced influence maximization aims to balance the influence maximization of multiple different entities in social networks and avoid the emergence of filter bubbles and echo chambers. Recently, an increasing number of studies have drawn attention to the study of balanced influence maximization in social networks and achieves success to some extent. However, most of them still have two major shortcomings. First, the previous works mainly focus on spreading the influence of multiple target entities to more users, ignoring the potential influence of the correlation between the target entities and other entities on information propagation in real social networks...

BACKGROUND AND OBJECTIVE: Postpartum Depression (PPD) is a frequently ignored birth-related consequence. Social network analysis can be used to address this issue because social media network serves as a platform for their users to communicate with their friends and share their opinions, photos, and videos, which reflect their moods, feelings, and sentiments. In this work, the depression of delivered mothers is identified using the PPD score and segregated into control and depressed groups...

BACKGROUND: Dimension reduction, especially feature selection, is an important step in improving classification performance for high-dimensional data. Particularly in cancer research, when reducing the number of features, i.e., genes, it is important to select the most informative features/potential biomarkers that could affect the diagnostic accuracy. Therefore, researchers continuously try to explore more efficient ways to reduce the large number of features/genes to a small but informative subset before the classification task...

This article introduces a network data set on the friendships and group work interactions among a convenience sample of 276 Czech Grade 6 students from twelve classrooms, supported by student-level demographic, literacy, motivation, and classroom communication data. Gathered longitudinally at the beginning and end of the 2021/2022 school year, the data provide a relational insight into the nature and evolution of early adolescents' friendships. Moreover, the data provide a unique relational and temporal insight into the verbal interaction of students during classroom group work...

BACKGROUND: Social media applications provide room for public interaction and forming communities, thus helping disseminate health-related information. Since 2010, World Hepatitis Day has been observed on July 28 with endorsement from the World Health Organization. This study aimed to ascertain the global digital impact of World Hepatitis Day on Twitter (an online microblogging social network) and on the web (web searches and news) to formulate evidence-based recommendations for promoting future policy development...

Metal-organic frameworks (MOFs), are porous crystalline structures comprising of metal ions or clusters intricately linked with organic entities, displaying topological diversity and effortless chemical flexibility. These characteristics render them apt for multifarious applications such as adsorption, separation, sensing, and catalysis. Predominantly, the distinctive properties and prospective utility of MOFs are discerned post-manufacture or extrapolation from theoretically conceived models. For empirical researchers unfamiliar with hypothetical structure development, the meticulous crystal engineering of a high-performance MOF for a targeted application via a bottom-up approach resembles a gamble...