Social Networking Sites Research Articles

Knowledge and practice of early gastric cancer screening among adults aged ≥ 45 years in China: a cross-sectional study

BackgroundAs the incidence of gastric cancer increases sharply in adults aged over 45 years, a better understanding of gastric cancer screening knowledge and practice is crucial to promote cancer-screening services. This study aimed to evaluate knowledge of early gastric cancer screening, adherence to screening, and perceived barriers hindering screening practices among adults aged ≥ 45 years in China.MethodsA multi-center, face-to-face, cross-sectional study was conducted in community sites in Shijiazhuang, China, through the distribution of structured questionnaires from August to September, 2022.ResultsOf the 1053 respondents, only 13.4% demonstrated a good understanding of early gastric cancer screening. While 64.0% knew that gastroscopy is the gold standard for screening (“how to screen”), only 19.9% were aware of the recommended starting age (“when to screen”). Moreover, less than half could correctly identify high-risk groups (“whom to screen”), with awareness ranging from 20.5% for those infected with H. pylori to 47.8% for those with gastric diseases. Independent factors related to higher screening knowledge included female sex (OR = 1.55, 95% CI = 1.01–2.38), higher education level (OR = 4.03, 95% CI = 2.68–6.06), being with a personal/family experience of gastric diseases (OR = 1.68, 95% CI = 1.12–2.52). In addition, only 23.4% of respondents underwent GC screening. The dominant barrier to early screening was the “absence of symptoms or signs”, followed by “fearing procedural discomfort”.ConclusionThis study highlights significant gaps in early gastric cancer screening knowledge and participation among middle-aged and elderly individuals in China. Addressing these gaps through culturally tailored health education campaigns is a critical strategy for increasing public awareness and participation.

Visualising the universe: The role of pictures in mediating people's relationship with outer space

The last decade has witnessed an increased interest in outer space among non-expert citizens of London; many astronomical societies have expanded, and telescopes and astronomical magazines have experienced pronounced growth in sales. Anthropology, as a discipline focused on the study of human culture, has recently provided new insights into the cultural dimensions involved in contemporary experiences of the universe. After spending two months among amateur astronomers at two London astronomical societies, I argue that pictures – understood from a material culture perspective – play a key role in shaping people's relationship with the universe. This relationship is currently influenced by new technologies that offer more accessible ways to capture and share pictures of the skies. Simultaneously, new social media apps have opened new digital platforms for sharing outer space pictures, introducing innovative visual ways to engage with it.

Awareness of Social Engineering Attacks and their Relation to the Ability to Persuade among users of Social Networking Sites

Awareness of Social Engineering Attacks and their Relation to the Ability to Persuade among users of Social Networking Sites

Attachment Avoidance Mediates the Relationship Between Relatedness Frustration and Social Networking Sites Addiction: Conscientiousness and Neuroticism as Moderators

Social Networking Sites Addiction (SNSA) has become increasingly prevalent among university students, posing significant challenges to their mental health and academic performance. The psychological mechanisms and personality traits contributing to this addiction are not yet fully understood. This study explored the mediating effect of attachment avoidance (AA) between relatedness frustration (RF) and SNSA, as well as the moderating roles of Conscientiousness and Neuroticism from the Big Five personality traits. Data were collected from 489 university students (M = 18.81, SD = 0.92) using the Relatedness Frustration Scale, Ten-Item Personality Inventory in Chinese, Experiences in Close Relationships Scale (ECR) Short Form, and Social Networking Sites Addiction Scale. The findings were as follows: (1) RF significantly predicted SNSA; (2) RF significantly predicted AA, which in turn significantly predicted SNSA, indicating a partial mediation; and (3) Conscientiousness and Neuroticism moderated the effect of RF on SNSA, with higher levels of these traits amplifying the positive effect of RF on SNSA. The study concluded that individuals facing RF may avoid real-life attachments and seek connections online, increasing the risk of SNSA, especially for those with high levels of Conscientiousness and Neuroticism.

Perspectives of midwives on respectful maternity care

BackgroundRespectful maternity care forms the foundation of maternity services; however, delivery of dignified, efficient, and effective care in these settings remains inconsistent. Research has identified several factors that influence respectful maternity care. To understand the South African context, these factors were explored and described from the perspectives of midwives. MethodsA qualitative descriptive inquiry was conducted, with participants recruited through snowball sampling on the social networking site Facebook. Semi-structured questions were used to collect data, to which participants responded in writing, detailing factors that influenced respectful care, including words and practices they associated with respectful maternity care. The data was analyzed using content analysis to identify common categories.ResultsTwenty-five responses from participants were analyzed; four categories and six sub-categories emerged as representations of respectful maternity care. The categories and sub-categories were as follows: healthcare professional behavior (ethical conduct and professional attributes related to education and training), managerial support (conducive work environment), interpersonal facet of care (characteristics of healthcare providers), and the birth environment (caring within the birth environment and client-centered care).ConclusionMidwives emphasized the importance of understanding respectful maternity care to ensure optimal outcomes for women, families, and communities. However, given the complexity of maternity care, it is crucial for policymakers, administrators, and midwives to comprehend and appreciate the various elements that define respectful care, as this understanding can significantly enhance its successful implementation.

Memes in Marketing: Impact on Advertising Literacy and Emotional Experience Among Adolescents

Declining digital marketing metrics often point to a trend of lower interest in advertising and sponsored content. Therefore, creators are finding other ways to spread the advertising message, particularly through native advertising, one option being the use of memes. Memes are an effective and very popular tool for reaching adolescents, but their use requires caution and an understanding of their dynamic and often unpredictable nature. The aim of this study is to investigate the impact of memes on social networking sites that have advertising content on adolescents' levels of advertising literacy. The study was conducted through a qualitative neuromarketing study and follow-up personal interviews with a sample of 24 respondents. The results indicate lower levels of advertising literacy among adolescents who, while recognizing the sales intent of the meme image, were unable to identify the sponsor. The results also confirmed that memes can evoke different emotions in adolescents, such as joy, but also anger and frustration. The research findings raise the concern that adolescents are not sufficiently able to navigate safely in the online environment, which is exploited by many companies in their sales techniques. Such adolescents can easily be deceived, misled. This has triggered the need for more intensive media literacy education on the one hand, and the introduction of consistent ethical principles on the other, i.e. on the advertisers' side. Received: 11 March 2024 / Accepted: 20 October 2024 / Published: 05 November 2024

STRUCTURAL AND FUNCTIONAL ASPECTS OF POLITICAL COMMUNICATION IN THE CONTEXT OF MODERN SOCIAL DEVELOPMENT

The article highlights the structural and functional features of political communication as a process of communicative interaction in the political sphere in the conditions of modern social development. It was determined that political communication is a communicative process of mutual exchange of political information and broadcasting of political discourse among political subjects, state administration bodies, civil society, aimed at achieving consensus in making political and managerial decisions, legitimizing power and maintaining the stability of the democratic political system through means mass communication, Internet social networks, informal contacts, etc. The leading functions of political communication in terms of its structural elements are distinguished: 1) subjects of political communication: citizens, state authorities and management, political parties, movements and associations, civil society institutions, associations and groups of users of social networks on the Internet etc; 2) feedback between the subjects of political communication, acting as a communicative interaction that takes on different forms of information exchange; 3) information message as a relevant political discourse; 4) channels and means of information transmission and two-way communication between subjects of political communication.

DC-SoC: Optimizing a Blockchain Data Dissemination Model Based on Density Clustering and Social Mechanisms

Due to its partially decentralized and highly scalable features, the consortium blockchain has currently overtaken other blockchain technologies as the one most frequently used and studied across various industries. However, performance issues such as low transaction efficiency and redundant communication processes continue to hinder the development of consortium blockchains. In the Hyperledger Fabric consortium blockchain system, transaction efficiency is largely influenced by the consensus protocol and broadcast protocol. This paper introduces a novel consortium blockchain network model, DC-SoC, focused on optimizing broadcast protocols. By incorporating the concept of density clustering, a stable propagation structure is established for the blockchain network, thus optimizing data dissemination in the Gossip protocol. Additionally, the concept of social networks is integrated, using trustworthiness scores and economic incentives to evaluate node security. The experimental results demonstrate that when DC-SoC is applied in a large-scale consortium blockchain environment, it significantly improves communication performance between nodes and ensures transmission reliability.

Implications of Self-Other Overlap for Cyber Dating Abuse in Young Adult Romantic Partners

Social network sites (SNSs) have brought about profound changes in the way people relate to others, including their romantic partners. Despite the advantages SNSs may have for building and managing romantic relationships, their use can be linked to risky behaviors within romantic relationships, such as the emergence of jealousy, control, and intrusiveness, i.e., cyber dating abuse (CDA) behaviors. The present study, in a sample of 315 Italian young adults involved in a romantic relationship (74.6 percent women and 25.4 percent men) aged 20 to 33 years (M = 24.17; SD = 2.60), explored CDA behaviors and their association with self-other overlap. Findings showed a positive association between self-other overlap and the frequency of CDA behaviors. That is, those who struggled to recognize their partners as different from themselves tended to control and enact intrusive behaviors toward them. This association, however, was moderated by the partners’ relationship duration, so that it was only significant for partners in a long-term relationship. The study expands our understanding of CDA behaviors in romantic relationships, contributing to identifying the conditions under which they are more likely to be perpetrated. In addition, it helps inform interventions for preventing risky behaviors within young adults’ romantic relationships.

Knowledge seeking in the context of social media mobile apps

Knowledge seeking in the context of social media mobile apps

Visual interpersonal communication on social network sites in romantic relationships

Visual interpersonal communication on social network sites in romantic relationships

Characteristics and treatment patterns of long-surviving patients with multiple myeloma: over 13 years of follow-up in the Connect® MM Registry

BackgroundOver the last 15 years, improvements in patient management and treatments have been associated with longer survival in patients with multiple myeloma (MM). The Connect MM Registry is a long-running, US, multicenter, prospective observational cohort study of patients with newly diagnosed MM (NDMM). We assessed the demographics, clinical characteristics, and treatment patterns of long-term survivors (LTS) enrolled in this registry. MethodsAdults with NDMM (N=3,011) were enrolled from 250 community, academic, and government sites across the US from 2009-2016. Baseline characteristics, treatment patterns, quality of life (QoL), and overall survival (OS) were examined among LTS, defined as patients with follow-up of ≥8 years after enrollment. ResultsAs of February 7, 2023, 518 patients were LTS and 2,493 were non-LTS. LTS were generally younger and had better performance status at enrollment compared with non-LTS. Most (65%) LTS received stem cell transplants and few (2%) experienced disease progression within 6 months of starting first line of therapy. At data cutoff, 63% of LTS were still on treatment at their most recent visit. QoL scores and QoL questionnaire completion rates were consistently higher among LTS than non-LTS. The estimated 8-year OS rate of all patients enrolled in the registry was 40%, comparable to an observed 8-year survival of 39% from the Surveillance, Epidemiology, and End Results (SEER) database. ConclusionThis analysis provides insights on long-surviving patients with MM using real-world data and therefore presents generalizability beyond data obtained in long-term follow-up of clinical trials, underscoring the need for longitudinal follow-up through registries. DisclosuresHoward R. Terebelo, James Omel, Lynne I. Wagner, James W. Hardin Brian G. Durie, Mohit Narang, Kathleen Toomey, and Rafat Abonour report serving on a scientific steering committee for Bristol Myers Squibb. Robert M. Rifkin reports serving on a scientific steering committee for Bristol Myers Squibb; employment, stock, and other ownership interests with McKesson; participation on data safety monitoring board for CARsgen; and advisory role with Amgen, Bristol Myers Squibb; Coherus BioSciences, Genmab, Fresenius Kabi, and Janssen. Sikander Ailawadhi reports serving on a scientific steering committee for Bristol Myers Squibb; consulting fees from BeiGene, Bristol Myers Squibb, Cellectar, GSK, Janssen, Pfizer, Regeneron, Sanofi, and Takeda; and research funding from AbbVie, Amgen, Ascentage, Bristol Myers Squibb, Cellectar, GSK, Janssen, Pharmacyclics, and Sanofi. Cristina J. Gasparetto reports serving on a scientific steering committee for Bristol Myers Squibb; support for travel from Bristol Myers Squibb, Karyopharm, and Sanofi; advisory role for Bristol Myers Squibb, Janssen, and Pfizer; and for Bristol Myers Squibb, Karyopharm, and Sanofi. Prashant Joshi, E. Dawn Flick, Edward Yu, and Ying-Ming Jou report employment and stock and other ownership interests with Bristol Myers Squibb. Hans C. Lee reports serving on a scientific steering committee for Bristol Myers Squibb; consulting fees from Allogene, Bristol Myers Squibb, Genentech, GlaxoSmithKline, Janssen, Monte Rosa Therapeutics, Pfizer, Regeneron, Sanofi, and Takeda; and grants or contracts from Amgen, Bristol Myers Squibb, GlaxoSmithKline, Janssen, Regeneron, and Takeda. Sundar Jagannath reports serving on a scientific steering committee for Bristol Myers Squibb; consulting fees from Bristol Myers Squibb, Janssen, Karyopharm Therapeutics, Legend Biotech, Regeneron Sanofi, and Takeda; support for travel from ASCO, ASH, and IMS; participation on data safety monitoring boards for Bristol Myers Squibb, Janssen, and Sanofi; and leadership or fiduciary role for ASH, IMS, and SOHO. MicroAbstractPatient characteristics, treatment patterns, quality of life, and survival were analyzed among long-surviving patients of multiple myeloma from the Connect® MM Registry. Long survivors were generally younger and healthier at diagnosis when compared with non-long survivors. The results provided insights beyond the long-term follow-up of clinical trials, indicating the importance of real-world longitudinal follow-up.

대학생의 디지털 리터러시 변화에 대한 종단연구: 잠재성장모형을 적용하여

The purpose of this study was to examine the change patten of college students’ digital literacy by using the data of ‘Korean Media Panel Data for the 12th(2021), 13the(2021), 14th(2023) year conducted by Korea Information Society Development Institute(KISDI). Four sub-competencies of information utilization, information acquisition, media utilization, and personal information recognition were selected as digital literacy competencies. The latent growth model was utilized to analyze longitudinal change with influence of independent variables. The major findings of this research were as followings. First, college student’s digital literacy showed linearly increased. Second, it was confirmed that the major(engineering sciences), SNS(social network service) and OTT(over-the-top media service) consumption behavior had a positive effect on the initial level and change in digital literacy, while gender had no significant differences in digital literacy. Third, the predictors(major, SNS and OTT consumption) had significant effects on information utilization, information acquisition. Based on the results of study, we suggest that it is necessary to care of non-science and Engineering Students. Also, it is necessary to provide opportunities and programs for individual student to use digital platforms and online contents.

Reaching the Voters: Parties’ Use of Google Ads in the 2021 German Federal Election

Election campaigns during the pandemic showcased the increased use of costly digital campaigning by parties. While many studies focus on the use of Facebook, X (formerly Twitter), and other social networking sites during elections, parties’ use of Google Ads remains widely unstudied. This is surprising given that parties spend a substantial proportion of their budget on Google Ads and Google reports on this spending and other details of the ads in its <em>Transparency Report</em>. Based on the equalisation vs. normalisation thesis, we identify party factors (size, age, government/opposition status, and electoral strongholds) that affect parties’ use of this instrument to a different degree in their campaigns. We aim to highlight parties’ use of Google Ads during the campaigns for the 2021 German Bundestag election, relying on the official data provided via Google’s Ad Library. We discuss both empirical work on the factors that determine the use of Google Ads and conceptual work on the merit and perils of such ads in democratic elections, and we present descriptive and exploratory findings of our deep dive into the archive of Google Ads.

Analysis of feature extraction techniques for sentiment analysis of tweets

Over the past few years, sentiment analysis has moved from social networking services like LinkedIn, Facebook, YouTube, Twitter, and online product-based reviews to determine public opinion or emotion using social media textual contents. The methodology includes data selection, text pre-processing, feature extraction, classification model, and result analysis. Text pre-processing is an important stage in structuring data for improved performance of our methodology. The feature extraction technique (FET) is a crucial step in sentiment analysis as it is difficult to obtain effective and useful information from highly unstructured social media data. A number of feature extraction techniques are available to extract useful features. In this work, popular feature extraction techniques including bag of words (BOW), term frequency and inverse document frequency (TF-IDF), and Word2vec are compared and analyzed for the sentiment analysis of social media contents. A method is proposed for processing text data from social media networks for sentiment analysis that uses support vector machine as a classifier. The experiments are carried on three datasets of different context namely US Airline, Movie Review, and News from Twitter. The results show that TF-IDF consistently outperformed other techniques with best accuracy of 82.33%, 92.31%, and 99.10% for Airline, Movie Review, and News datasets respectively. It is also found that the proposed method performed better than some existing methods.

Social Networking Sites (SNS) for Japanese Language Learning

Social Networking Sites (SNS) have become an integral part of modern society, influencing various aspects of life, including education. SNS facilitates interactive, collaborative, and reflective learning experiences in language learning. This study aims to evaluate the use of SNS in enhancing learning inside and outside Japanese language classrooms. The research was conducted using a qualitative approach with a survey method, utilizing a questionnaire distributed via Google Forms. Quantitative and qualitative data collected from 85 Japanese Language Education Study Program students were analyzed and presented narratively. The data were examined through the lens of SNS use in foreign language learning and its impact on language acquisition. The results reveal that most students frequently use SNS platforms such as YouTube, Instagram, and Twitter for learning Japanese, both for classroom materials and independent study. Additionally, students reported that SNS use has improved their reading, writing, listening, and speaking skills in Japanese. Moreover, SNS has been identified as a motivational tool, fostering students’ confidence in using the language orally and in writing. These findings provide valuable insights for future research on using SNS as a learning medium in Japanese language education.

Why Are Foodies Active on Social Network Services? An Exploratory Study on Foodies’ Influence on Social Media

As social media continues to gain traction in the food industry, this study explored how cooking and dining-out behaviors and social media use differ depending on the foodie tendencies of consumers, particularly Korean Millennial and Gen Z consumers. Additionally, this study considered the effect of foodie tendencies on active social media usage. Based on the Foodie Index, two groups were identified: high and low. The high group scored higher than the low group on foodie knowledge and spending, food interest, and time commitment. Comparison of the food, cooking, and dining-out behaviors of both groups revealed a significantly greater frequency of cooking and a higher proportion of using their own ingredients, even when dining alone, in the high group. Analysis of social media use characteristics also demonstrated significantly higher scores for the high group than the low group in terms of the degree of use, average daily usage time, checking frequency, and use of social media recommendations when cooking and purchasing food. Furthermore, foodie inclination significantly influenced active usage behavior, as users shared informative content and frequently posted articles and photos. This study found that foodies play a leading role in producing food-related information by actively using and sharing social media. Considering this ripple effect, consumers’ foodie tendencies can be used as an important measure in food marketing-related research.

Identification of active ingredients in Naomaitai capsules using high-resolution mass spectrometry unite molecular network analysis and prediction of their action mechanisms.

Although Naomaitai capsule (NMC) is widely used in clinical practice and has a good curative effect for cerebral infarction, its material basis and mechanism of action remain unclear. In this study, ultra-high-performance liquid chromatography (UHPLC) coupled with quadrupole Orbitrap MS technology was used to analyse the in vivo and in vitro components of NMC, and the Global Natural Products Social Molecular Networking website was used to further analyse the components of NMC. Next, systems biology approaches were employed to investigate the mechanism of action of NMC. Finally, molecular docking technology was used to verify the network pharmacological results. In total, 177 compounds were identified in vitro, including 65 terpenoids, 62 flavonoids, 25 organic acids and 11 quinones. 64 compounds were identified in the blood of mice, and the main active components included ginkgolide C, ginkgolide A, ligustilide, tanshinone IIB, olmelin, emodin and puerarin. The main targets in vivo included TP53, SRC, STAT3, PIK3CA and PIK3R1. In conclusion, this study has revealed that NMC acts on multiple targets in the body through various active components, exerting synergistic effects in the treatment of CI. Its mechanism of action may involve inhibiting neuronal apoptosis, oxidative stress and inflammatory responses as well as reducing cerebral vascular permeability and promoting cerebral vascular regeneration.

A conceptual framework for digital health marketing strategies to enhance public health outcomes in underserved communities

This paper proposes a conceptual framework for integrating digital health marketing strategies with public health initiatives to enhance healthcare access and outcomes in underserved communities. The framework focuses on leveraging digital marketing tools such as social media, mobile applications, email campaigns, and search engine optimization to disseminate critical health information, promote preventive measures, and engage communities in healthier behaviors. It addresses the persistent challenges faced by underserved populations, including limited healthcare access, low health literacy, and cultural barriers, by utilizing the accessibility and broad reach of digital channels. The proposed framework incorporates three core components: (1) Health Information Dissemination, which explores the use of targeted digital campaigns to provide culturally relevant and accessible health education; (2) Community Engagement, which leverages interactive platforms such as social media and mobile apps to foster participation in preventive healthcare initiatives and healthy lifestyle practices; and (3) Behavioral Change Promotion, which emphasizes using digital tools to influence health behaviors through personalized messaging, reminders, and virtual support groups. By integrating digital marketing strategies into public health programs, the framework aims to improve healthcare outcomes by increasing awareness of preventive measures, enhancing early diagnosis, and promoting disease management. It also underscores the role of data analytics in refining outreach efforts by identifying specific health needs, tracking engagement, and measuring the effectiveness of interventions. This conceptual framework holds promise for healthcare providers, policymakers, and digital marketers seeking to enhance public health outcomes in underserved communities. It provides a structured approach to combining the strengths of digital marketing with public health goals, creating more inclusive, accessible, and effective health interventions. Future research and case studies can build on this model to refine digital health marketing strategies and assess their long-term impact on public health in underserved populations.

Social Media Insight: Predicting Self-Harm Trends

Poisoning or injuring oneself can cause death or injury without intent. This is self-harm. Self-harm harms the perpetrators and the nation's economy. Studies have linked increased urbanization in emerging nations to rising self-harm and new technology. National self-harm patterns may be important for policymakers and public health experts to predict. This would allow them to immediately fix issues or avoid disasters. Studies have forecasted population-level self-harm patterns in many nations using simple statistics. In certain nations, prior data may be scarce or insufficient to make reliable projections. This makes it tougher to FAST assess and anticipate national self-harm. This essay proposes FAST, a technique that uses mental indicators from social media to forecast national self-harm trends. These markers can represent community mental health and help forecast self-harm patterns. Language-agnostic algorithms are taught to first identify mental indicators in gathered social media communications. These signals form multivariate time series. The time-delay embedding method then places these events in time. Last, many machine learning regressors are tried for future prediction. Tweets with 12 mental indicators may predict self-harm-related fatalities and injuries, according to a Thailand research. The suggested method predicted self-harm deaths and injuries. Better than ARIMA baseline by 43.56% and 36.48%. We think our research is the first to predict national self-harm trends using social media data. The findings improve self-harm prediction and establish the framework for new social network-based apps that forecast socioeconomic aspects. We used the top machine learning algorithms, Decision Tree and Voting Regressor. We found less MAE mistakes with these techniques.