Online Social Networking Sites Research Articles

Learning through Participation

Abstract Social media play increasingly important roles in changing young people’s learning styles. The most significant implication for moral and citizenship education would be that young people nowadays are employing social media for cybercivic participation and learning, constructing to both online and offline communities. This paper, based on a virtual ethnographic study, examines how Chinese university students participate in civic discussions and activities by the use of online forums and social network sites. It further explores youth capabilities of learning to be responsible, reciprocal, and reflective citizens. The paper presents three potential learning paradigms, namely dutiful, actualising, and reflective cybercivic learning, and argues that each paradigm has its advantages and limitations in developing moral and civic knowledge, values, and skills. To integrate three learning paradigms into the institutional education system would be an innovation of moral and citizenship education in the age of social media.

Grappling With the COVID-19 Health Crisis: Content Analysis of Communication Strategies and Their Effects on Public Engagement on Social Media.

BackgroundThe coronavirus disease (COVID-19) has posed an unprecedented challenge to governments worldwide. Effective government communication of COVID-19 information with the public is of crucial importance.ObjectiveWe investigate how the most-read state-owned newspaper in China, People’s Daily, used an online social networking site, Sina Weibo, to communicate about COVID-19 and whether this could engage the public. The objective of this study is to develop an integrated framework to examine the content, message style, and interactive features of COVID-19–related posts and determine their effects on public engagement in the largest social media network in China.MethodsContent analysis was employed to scrutinize 608 COVID-19 posts, and coding was performed on three main dimensions: content, message style, and interactive features. The content dimension was coded into six subdimensions: action, new evidence, reassurance, disease prevention, health care services, and uncertainty, and the style dimension was coded into the subdimensions of narrative and nonnarrative. As for interactive features, they were coded into links to external sources, use of hashtags, use of questions to solicit feedback, and use of multimedia. Public engagement was measured in the form of the number of shares, comments, and likes on the People’s Daily’s Sina Weibo account from January 20, 2020, to March 11, 2020, to reveal the association between different levels of public engagement and communication strategies. A one-way analysis of variance followed by a post-hoc Tukey test and negative binomial regression analysis were employed to generate the results.ResultsWe found that although the content frames of action, new evidence, and reassurance delivered in a nonnarrative style were predominant in COVID-19 communication by the government, posts related to new evidence and a nonnarrative style were strong negative predictors of the number of shares. In terms of generating a high number of shares, it was found that disease prevention posts delivered in a narrative style were able to achieve this purpose. Additionally, an interaction effect was found between content and style. The use of a narrative style in disease prevention posts had a significant positive effect on generating comments and likes by the Chinese public, while links to external sources fostered sharing.ConclusionsThese results have implications for governments, health organizations, medical professionals, the media, and researchers on their epidemic communication to engage the public. Selecting suitable communication strategies may foster active liking and sharing of posts on social media, which in turn, might raise the public’s awareness of COVID-19 and motivate them to take preventive measures. The sharing of COVID-19 posts is particularly important because this action can reach out to a large audience, potentially helping to contain the spread of the virus.

Interrelationship between Interpersonal Interaction Intensity and Health Self-Efficacy in People with Diabetes or Prediabetes on Online Diabetes Social Platforms: An In-Depth Survey in China.

Objective: The peer interaction–based online model has been influential in the recent development of diabetes management. This model “extends and innovates” the traditional mode of doctor–patient guidance, transforming it into a mode in which both doctor–patient guidance and patient–patient interaction coexist; this new mode has the added advantage of offering “extended continual intervention.” This study contributes to research on extending diabetes management models by investigating how patients with diabetes or prediabetes interact in online health communities, focusing on the interrelationship between self-efficacy characteristics and online participation during patient–patient interactions. Methods: In this cross-sectional study, participants with diabetes of various severities completed an electronic questionnaire, which was formulated with a revised classical scale. The questionnaire was disseminated through diabetes online health communities. Its content covered the respondent’s general condition, self-evaluation of their self-efficacy, and participation in online health communities, specifically with respect to factors such as the time spent in online information each day, the number of groups joined, and the extent of interaction in diabetes online health communities, etc. The main observation indicators were the participants’ self-efficacy, their extent of online participation, and the characteristics of online health communities. Descriptive statistics, chi-square test, linear trend estimation, and ordinal logistic regression were used to explore the relationship between the three indicators. Results: The self-efficacy scores ( ± s) were 51.9 ± 9.12, and 59.1% of interviewed participants had self-efficacy scores greater than the mean. Overall, most participants (96%) considered online diabetes social platforms to be helpful. Groups differed with respect to interaction mode, which indicated that people with high self-efficacy tend to employ various modes of interaction. Participants with high self-efficacy were also more likely to live in cities (p < 0.05) and be married (p < 0.05) and tended to spend more time paying attention to group information (p < 0.05), spend more time viewing group information (p < 0.05), and have a greater degree of interaction with group members (p < 0.05). Information sources for the different grades of participants was primarily obtained from social media. Conclusion: Among people with diabetes, the frequency and intensity of online interaction might positively affect self-efficacy and, by implication, diabetes self-management. Diabetics with high self-efficacy also tend to have positive online interaction and adopt different ways of interaction. In addition, the diabetes information sources of the respondents mainly come from social networks, most of the respondents think that online social networking sites have a positive impact on diabetes self-management, which shows that social network plays an important role in diabetes information source of diabetics. However, the design of online health communities has room for improvement, specifically with respect to the provision of information that patients require. As an interesting side note, among people with diabetes or prediabetes, those who lived in urban area and were married, those who paid more attention to group information, and those who actively participated in interactions tended to have relatively high self-efficacy. The results suggest that people with diabetes have higher-quality self-care when they engage in online health community interactions; such benefits cannot be obtained from treatment in a hospital. In general, enhanced self-efficacy in people with diabetes enables them to more readily acquire diabetes-related knowledge. Online interaction with diabetics, who has the same experience, can not only get more information, but also have a sense of identity and belonging, which enhances self-efficacy and further urges them to actively participate in online interaction. Therefore, online health communities are an important supplement to the clinical treatment of diabetes mellitus and clinicians can take advantage of the educational function of online diabetes groups in their provision of tailored diabetes interventions and take into account the factors that affect the self-efficacy of diabetics (including the frequency and intensity of online interaction, age, marital status, residential area, etc.), to provide tailored diabetes interventions for diabetics. Such a use of online diabetes groups can strengthen diabetes self-management.

‘Do digital technologies matter? How hyperlocal media is re-configuring the media landscape of a Russian province’

The increase of internet penetration across Russia has reduced entry barriers for individuals and companies who want to report locally. New digital technologies have given rise to many semi-professional local media projects, so-called ‘hyperlocal media’ (Metzgar et al., 2011; Tenor, 2018), created on various online platforms and social networking sites. Websites, blogs, and social media groups (the so-called ‘pabliki’ in Russian) on the popular social networking site VKontakte have opened up new access routes to local news, both for ordinary citizens and the authorities, but have also become a challenge for traditional local media. This article investigates how the media landscape changes in response to digital technologies in a provincial town of nearly 40,000 in the European part of Russia. More specifically, the article investigates how professional journalists from traditional media and practitioners from hyperlocal media sites understand the influence of digital technologies on the aims and work practices of media in a Russian province. The study is based on in-depth interviews with the editors of traditional local media (e.g. print newspapers) and owners of new hyperlocal media initiatives. The research explores different approaches to the ways in which two groups of media actors understand and make use of the internet and digital technologies. However, within peculiar Russian media model, these differences have led to collaborative rather than competitive relations between the two groups.

Identifying spammers and fake users identification in online social networking sites

Online social networking sites are new platforms for spreading spammers and fake news for attackers. Recently, the detection of spammers and identification of fake users on Twitter has become a common area of research in contemporary online social Networks (OSNs). In this paper, we perform a review of techniques used for detecting spammers on Twitter. Twitter spam detection approaches is presented that classifies the techniques based on their ability to detect: (i) fake content, (ii) spam based on URL, (iii) spam in trending topics, and (iv) fake users. The presented techniques are also compared based on various features, such as user features, content features, graph features, structure features, and time features.

Effect of Supervised and Unsupervised Algorithm for Cross Domain Sentiment Analysis

Today we are living in the "information age" where data is the capital of the new economy. With the rapidly growing data every day on online portals and social networking websites, today industries are collecting and analyzing more data than before. Though data is readily available but finding valuable insights out of it is a real task. With easy accessibility of the data, new technologies, and a cultural shift towards data-driven decision making drives the need for Sentiment Analysis (SA) and makes it relevant in most of the domains like politics, marketing, healthcare, etc. This rapidly increasing information on different domains has motivated researchers to develop a cross-domain sentiment analysis model. For the development of this model, we have analyzed the performance of supervised and unsupervised models on benchmark datasets for the cross-domain analysis. The models chosen for the supervised is the Support Vector Machine (SVM) and for the unsupervised approach we have used a combination of Vader wherein the testing results showed that the supervised algorithms performed well in comparison to the unsupervised algorithm.

Fathers of Children With Congenital Heart Disease: Sources of Stress and Opportunities for Intervention.

To examine sources of stress for fathers of children with congenital heart disease and opportunities for intervention to prevent or reduce paternal mental health problems. Qualitative study using online crowdsourcing, an innovative research methodology to create an online community to serve as a research sample. Yammer, an online social networking site. Geographically diverse sample of 70 parents (25 fathers and 45 mothers) of young children with congenital heart disease. Participants joined a private group on Yammer and responded to 37 open-ended study questions over a 6-month period. Qualitative data were coded and analyzed using an iterative process, and themes regarding sources of stress for fathers of children with congenital heart disease and opportunities for intervention were identified. Four broad themes regarding sources of stress for fathers of children with congenital heart disease emerged from the qualitative data from both mothers and fathers: societal expectations for fatherhood and standards of masculinity, balancing work and family responsibilities, feeling overlooked as a partner in care, and lack of father supports. To begin to address these sources of stress, participants recommended that care teams acknowledge and normalize the impact of congenital heart disease on fathers, provide support for balancing work and family responsibilities, recognize and promote father knowledge and engagement, and provide formal and informal supports for fathers of children with congential heart disease. Fathers of children with congenital heart disease experience unique sources of stress in the absence of targeted interventions to meet their needs. Care teams play an important role in acknowledging the experiences of fathers and including and engaging fathers in care.

Unattached and unconvinced: Australian non‐partisans

AbstractPolitical party identification is a strong predictor of political behaviour and social attitudes in advanced industrialised democracies. Australian Election Study data show declining identification with major parties over time, and that working‐class Australians, those who do not identify with any class, the secular and the politically uninterested are most likely to be non‐partisans. However, national samples rarely allow for detailed analysis of younger people, given the low numbers of younger people they contain. Longitudinal data from the Social Futures and Life Pathways (“Our Lives”) project enable us to focus upon young Australians aged 24 living in the state of Queensland. The Queensland data show that younger non‐partisans tend to lack post‐secondary education, are on lower incomes, are less interested in politics and, importantly, have non‐aligned parents. Nationally, non‐partisans were less likely than partisans to pay attention to politics during the 2016 Federal Election, but more likely to decide how to vote on the day of the Federal Election and more likely than partisans to vote informal. Younger non‐partisans were also less likely to engage in non‐electoral political actions, such as signing e‐petitions or posting in online forums or social networking sites.

A psychometric approach to assessments of problematic use of online pornography and social networking sites based on the conceptualizations of internet gaming disorder

BackgroundThe problematic use of online gaming, social networking sites (SNS) and online pornography (OP) is an evolving problem. Contrary to the problematic use of SNS and OP, Internet gaming disorder (IGD) was included in the new edition of the Diagnostic and statistical manual of mental disorders (DSM-5) as a condition for further study. The present study adapted the criteria for IGD to the problematic use of SNS and OP by modifying a validated questionnaire for IGD (Internet Gaming Disorder Questionnaire: IGDQ) and investigating the psychometric properties of the modified versions, SNSDQ and OPDQ.MethodsTwo online samples (SNS: n = 700, 25.6 ± 8.4 years, 76.4% female; OP: n = 700, 32.9 ± 12.6 years, 76.7% male) completed the SNSDQ/OPDQ, the Brief Symptom Inventory (BSI) and the short Internet Addiction Test (sIAT) and provided information on their SNS/OP use. Standard item and reliability analyses, exploratory and confirmatory factor analyses and correlations with the sIAT were calculated. Problematic and non-problematic users were compared.ResultsThe internal consistencies were ωordinal = 0.89 (SNS) and ωordinal = 0.88 (OP). The exploratory factor analyses extracted one factor for both questionnaires. Confirmatory factor analyses confirmed the results. The SNSDQ/OPDQ scores correlated highly with the sIAT scores and moderately with SNS/OP usage time. Of the users, 3.4% (SNS) and 7.1% (OP) lay above the cutoff for problematic use. Problematic users had higher sIAT scores, used the applications for longer and experienced more psychological distress.ConclusionOverall, the results of the study indicate that the adaption of the IGD criteria is a promising approach for measuring problematic SNS/OP use.

Social Media Fake Account Detection for Afan Oromo Language using Machine Learning

A social networking service serves as a platform to build social networks or social relations among people who, share interests, activities, backgrounds, or real life connections. A social network service is generally offered to participants who registers to this site with their unique representation (often a profile) and one’s social links. Most social network services are web-based and provide means for users to interact over the Internet. (M. Smruthi, , February 2019).Online social networking sites became an important means in our daily life. Millions of users register and share personal information with others. Because of the fast expansion of social networks, public may exploit them for unprincipled and illegitimate activities. As a result of this, privacy threats and disclosing personal information have become the most important issues to the users of social networking sites. The intent of creating fake profiles have become an adversary effect and difficult to detect such identities/malicious content without appropriate research. The current research that have been developed for detecting malicious content, primarily considered the characteristics of user profile. Most of the existing techniques lack comprehensive evaluation. In this work we propose new model using machine learning and NLP (Natural Language Processing) techniques to enhance the accuracy rate in detecting the fake identities in online social networks. We would like to apply this approach to Facebook by extracting the features like Time, date of publication, language, and geo position. (Srinivas Rao Pulluri1, A Comprehensive Model for Detecting Fake Profiles in Online Social Networks, 2017) DOI: 10.7176/NMMC/90-01 Publication date: May 31 st 2020

Problematic social media use is associated with increased risk-aversion after negative outcomes in the Balloon Analogue Risk Task.

Around the world, people display maladaptive, problematic use of online social networking sites (SNSs), like Facebook, Snapchat, and Instagram. The symptoms of this problematic SNS use are similar to symptoms of substance use and behavioral addictive disorders, such as relapse when attempting to quit. Individuals with substance use and behavioral addictive disorders also display increased risk-taking when making decisions, but little research has investigated decision making with respect to problematic SNS use. We therefore assessed risky decision making and problematic SNS use by utilizing the Balloon Analogue Risk Task (BART). In line with previous research on behavioral addictive disorders, we hypothesized that greater problematic SNS use would be linked with greater risk-taking. To address our hypothesis, we conducted three studies in which we administered the Bergen Social Media Addiction Scale to assess problematic SNS use and related scores to BART performance. Collectively, and counter to our initial hypothesis, we found a negative association between problematic SNS use and risk-taking. Specifically, the more problematic one's SNS use, the less risk they took, but this risk aversion only occurred after receiving negative feedback on previous decisions and then encountering a situation with less actual risk. Implications of this novel finding are discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Displaying things in common to encourage friendship formation: A large randomized field experiment

Friendship formation is of central importance to online social network sites and to society, but can suffer from significant and unequal frictions. In this study, we demonstrate that social networks and policy makers may use an IT-facilitated intervention – displaying things in common (TIC) between users (mutual hometown, interest, education, work, city) – to encourage friendship formation, especially among people who are different from each other. Displaying TIC may update an individual’s belief about the shared similarity with another and reduce information friction that may be hard to overcome in offline communication. In collaboration with an online social network, we design and implement a randomized field experiment, which randomly varies the prominence of different types of things in common information when a user (viewer) is browsing a non-friend’s profile. The dyad-level exogenous variation, orthogonal to any (un)observed structural factors in viewer-profile’s network, allows us to cleanly isolate the role of individuals’ preference for TIC in driving network formation and homophily. We find that displaying TIC to viewers may significantly increase their probability of sending a friend request and forming a friendship, and is especially effective for pairs of people who have little in common. Such findings suggest that information intervention is a very effective and zero-cost approach to encourage the formation of weak ties, and also provide the first experimental evidence on the crucial role of individuals’ preference (versus structural embeddedness) in network formation. We further demonstrate that displaying TIC could improve friendship formation for a wide range of viewers with different demographics and friendship status, and is more effective when the TIC information is more surprising to the viewer. Our study offers actionable insights to social networks and policy makers on the design of information intervention to encourage friendship formation and improve the diversity of the friendship, at both an aggregate and an individual level.

Learning Visual Elements of Images for Discovery of Brand Posts

Online Social Network Sites have become a primary platform for brands and organizations to engage their audience by sharing image and video posts on their timelines. Different from traditional advertising, these posts are not restricted to the products or logo but include visual elements that express more in general the values and attributes of the brand, called brand associations. Since marketers are increasingly spending time in discovering and re-posting user generated posts that reflect the brand attributes, there is an increasing demand for such discovery systems. The goal of these systems is to assist brand experts in filtering through online collections of new user media to discover actionable posts, which match the brand value and have the potential to engage the consumers. Driven by this real-life application, we define and formulate a new task of content discovery for brands and propose a framework that learns to rank posts for brands from their historical timeline. We design a Personalized Content Discovery (PCD) framework to address the three challenges of high inter-brand similarity, sparsity of brand--post interactions, and diversification of timeline. To learn fine-grained brand representation and to generate explanations for the ranking, we automatically learn visual elements of posts from the timeline of brands and from a set of brand attributes in the domain of marketing. To test our framework we use two large-scale Instagram datasets that contain a total of more than 1.5 million image and video posts from the historical timeline of hundreds of brands from multiple verticals such as food and fashion. Extensive experiments indicate that our model can effectively learn fine-grained brand representations and outperform the closest state-of-the-art solutions.

Social Media Fake Account Detection for Afan Oromo Language using Machine Learning

A social networking service serves as a platform to build social networks or social relations among people who, share interests, activities, backgrounds, or real life connections. A social network service is generally offered to participants who registers to this site with their unique representation (often a profile) and one’s social links. Most social network services are web-based and provide means for users to interact over the Internet. (M. Smruthi, , February 2019).Online social networking sites became an important means in our daily life. Millions of users register and share personal information with others. Because of the fast expansion of social networks, public may exploit them for unprincipled and illegitimate activities. As a result of this, privacy threats and disclosing personal information have become the most important issues to the users of social networking sites. The intent of creating fake profiles have become an adversary effect and difficult to detect such identities/malicious content without appropriate research. The current research that have been developed for detecting malicious content, primarily considered the characteristics of user profile. Most of the existing techniques lack comprehensive evaluation. In this work we propose new model using machine learning and NLP (Natural Language Processing) techniques to enhance the accuracy rate in detecting the fake identities in online social networks. We would like to apply this approach to Facebook by extracting the features like Time, date of publication, language, and geo position. (Srinivas Rao Pulluri1, A Comprehensive Model for Detecting Fake Profiles in Online Social Networks, 2017) DOI: 10.7176/NMMC/90-01 Publication date: May 31 st 2020

Evaluating Customer Trust towards Online SNSs sellers using Fuzzy AHP

Trust plays a vital role in social commerce due to the inadequacy of physical interaction and experience during the customer-seller transaction. Various studies were drawn in the literature targeting the investigation of the influence criteria related to trust using statistical analysis approach. However, little attention has been paid on the importance of the criteria in evaluating customer trust toward online sellers that used Social Network Sites (SNSs) as business platforms. In this study, the Fuzzy AHP (FAHP) method, an extension of the Analytical Hierarchy Process (AHP) was adopted to determine the importance of criteria in evaluating customer’s trust towards online SNSs sellers. The results of FAHP were then compared against the result of AHP, which both methods’ results similarities and differences were also presented and discussed.

TWEEZER – Tweets Analysis

Twitter is one in all the foremost used applications by the people to precise their opinion and show their sentiments towards different occasions. Sentiment analysis is an approach to retrieve the sentiment through the tweets of the general public. Twitter sentiment analysis is application for sentiment analysis of information which are extracted from the twitter(tweets). With the assistance of twitter people get opinion about several things round the nation .Twitter is one such online social networking website where people post their views regarding to trending topics .It s huge platform having over 317 million users registered from everywhere the globe. a decent sentimental analysis of information of this huge platform can result in achieve many new applications like – Movie reviews, Product reviews, Spam detection, Knowing consumer needs, etc. during this paper, we used two specific algorithm –Naive Bayes Classifier Algorithm for polarity Classification & Hashtag classification for top modeling. this system individually has some limitations for Sentiment analysis. The goal of this report is to relinquish an introduction to the present fascinating problem and to present a framework which is able to perform sentiment analysis on online mobile reviews by associating modified naive bayes means algorithm with Naive bayes classification.

Exploring the Structure of Social Media Network with the Concepts of Graph Theory

Millions of people use online social networking sites such as Facebook, Twitter, WhatsApp, Instagram etc. Nowadays, social media is very popular among all of us especially young generation and has become a vital part of our life. Just like a graph is made up of vertices and edges , a social media network is made up of persons or communities where each person or community represents the vertex of the social graph and the adjacency of the vertices ( edges ) is determined via friendship, common interest, common liking etc. In this paper we try to show the use of some graphical parameter in social graph so that the many properties of social media network can be reflected through graph. We have also shown how domination number plays an important role in social graph.

Influence of Online Sources and SocialNetworking Sites on Breastfeeding Rate andPractices in Jordan

Objective: This study asses the influence of using mobile health in supporting breastfeeding through online sources and Social Network Sites (SNS) among pregnant and lactating mothers on EBF rates and practices at one and two months postpartum. Design: A cross-sectional study with initial face-to-face interviews using structured questionnaire followed up with telephone interviews at one and two months postpartum was conducted at University Hospital over two months period. A convenient sample of 181. Jordanian women in their third trimester of pregnancy was recruited. The included data were: personal characteristics, breastfeeding intention and rate at 1 and 2 months, and questions about the use of online researching or different SNS resources, in providing necessary information for breastfeeding, along with how much the information was trusted and if it had an impact on BF practices. Breastfeeding status and use of online resources were assessed at the initial and follow-up Interviews. Results: Online sources were used by 74% of participants. They most often used Google (44%), followed by Facebook (24.6%), as significant sources of obtaining and sharing information with others for breastfeeding support. Moreover, 82.5% of those users did so before giving birth, and were overwhelmingly confident (92.5%) in the accuracy of the obtained information. Users (n=134) were significantly more likely than non-users (n=47) to indicate that online sources enhanced breastfeeding practices and influenced their decision to continue EBF. Using these sites during pregnancy was associated with a significantly higher EBF rate among users at the first month and second month postpartum respectively. Conclusion: The study demonstrated high use of online and SNS resources that enhanced BF practices and rate at one and two months of age. In areas where breastfeeding programs are lacking, there is a need to design interactive mobile health platforms to motivate women to engage in breastfeeding during pregnancy.

Malaysian Private University Students’ Perception of Online Discussion Forums: A Qualitative Enquiry

The continuous advancement in technology has transformed physical learning platforms into digital spaces in higher education. In Malaysia, instructors and students are gradually adopting the e-learning or blended-learning approach by using online discussion forums (e.g. BlackBoard) or social networking sites (e.g. Facebook groups) to engage students’ participation in courses and encourage self-directed learning. This study presents a qualitative view of students’ perception of engaging in online discussion forums in a synchronous learning environment, and their views on the positive and negative aspects of using online discussion forums for learning. Results indicate that students perceive autonomy and sense of belongingness in the online community as main factors that influence their voluntary and active participation in the online discussion forums. Technical challenges remain as a key factor in determining students’ interests to utilize online discussion forums for learning. While future research is needed to assess the sentiments of Malaysian students in online learning, this study was intended to provide Malaysian instructors and higher education institutions a preview on the sentiments of students towards online learning to better improve the aspects of technical, pedagogical methods and policies for online learning as the nation moves towards Education 4.0.

She shares, but he does not: Gender differences in the sharing of charity‐related content on social networking sites

AbstractOnline social networks are widely used methods of communication. This research examines gender differences in people's tendency to post charity‐related messages. In general, compared to males, females show more empathic concerns with online charity‐related messages, which increases their willingness to post messages on their online social networking sites. However, message framing is key. Females' higher tendency only holds for charity messages that focus on benefits to others or the feelings of others, not for messages that are self‐focused. This research also identifies one way of improving men's willingness to post. Messages that are framed by focusing on negative consequence appeals can increase empathic concerns, which can increase males' willingness to share online charity messages on online social networking sites.