Journal articles on the topic 'Online social networks – Research'
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Willinger, Walter, Reza Rejaie, Mojtaba Torkjazi, Masoud Valafar, and Mauro Maggioni. "Research on online social networks." ACM SIGMETRICS Performance Evaluation Review 37, no. 3 (January 21, 2010): 49–54. http://dx.doi.org/10.1145/1710115.1710125.
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Walczak, Steven. "Artificial Neural Network Research in Online Social Networks." International Journal of Virtual Communities and Social Networking 10, no. 4 (October 2018): 1–15. http://dx.doi.org/10.4018/ijvcsn.2018100101.
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Artificial neural networks are a machine learning method ideal for solving classification and prediction problems using Big Data. Online social networks and virtual communities provide a plethora of data. Artificial neural networks have been used to determine the emotional meaning of virtual community posts, determine age and sex of users, classify types of messages, and make recommendations for additional content. This article reviews and examines the utilization of artificial neural networks in online social network and virtual community research. An artificial neural network to predict the maintenance of online social network “friends” is developed to demonstrate the applicability of artificial neural networks for virtual community research.
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Melton, James, Robert Miller, and Michelle Salmona. "Online Social Networks." International Journal of Information Systems and Social Change 3, no. 2 (April 2012): 24–38. http://dx.doi.org/10.4018/ijissc.2012040102.
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Previous research has shown that many college students in the United States post content to social networking sites that they know would be considered inappropriate by employers and other authority figures. However, the phenomenon has not been extensively studied in cross-cultural context. To address this knowledge gap, a survey of college students in Australia, Denmark, the United Kingdom, and the United States was conducted. The study found a universal tendency among the four groups: students knew the content they were posting would be considered inappropriate by employers and other authority figures, but they chose to post it anyway. The article also reports on differences in the way this tendency was manifested and on related aspects of social networking across cultures, including decisions about privacy and information disclosure.
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Agadullina, E. R. "Social networks user: current research." Современная зарубежная психология 4, no. 3 (2015): 36–46. http://dx.doi.org/10.17759/jmfp.2015040305.
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The purpose of this article is to review current research studies focusing on the users of Facebook and their behaviors in social networks. This review is organized into two sections: 1) social-demographic characteristics (Age, Gender, Nationality); 2) personality characteristics (Neuroticism, Extraversion, Openness-to-Experience, Agreeableness, Conscientiousness, Narcissism, Self-esteem). The results showed that the information in the personal profile and online behavior are strongly connected with socio-demographic and personality characteristics
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Xiong, Junli, and Huayi Huang. "Research on Information Leakage Tracking Algorithms in Online Social Networks." Computational Intelligence and Neuroscience 2022 (October 4, 2022): 1–11. http://dx.doi.org/10.1155/2022/5634385.
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An online social network is a platform where people can communicate with friends, share information, speed up business development, and improve teamwork. A large amount of user privacy information existing in real social networks is leaked from person to person, and this issue has hardly been studied. With the rapid expansion of the network, the issue of privacy protection has received increasing attention. So far, many privacy protection methods including differential protection algorithms, encryption algorithms, access control strategies, and anonymization have been researched and applied. Information leakage means that the information shared by the user is disseminated or downloaded by his friends without the user’s consent, and the transmission of private information will not be recorded. In order to track and find out the ways and methods of information leakage, this article adopts an unusual method, namely, the probability judgment based on trust. By screening the similarities between users, past information exchanges, and the topology of social networks, a trust model is established to evaluate and estimate the degree of trust between users. According to the rating information privacy of friends’ trust, an information dissemination system is established, which can be applied to online social networking platforms to reduce the risk of information leakage, thereby ensuring the security of users’ private information. At the same time, this paper expands the transmission system model without user authorization and proposes a fingerprint-based deterministic leak tracking algorithm.
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Tauginienė, Loreta, and Rima Kalinauskaitė. "Participation of doctoral students in online social networks." Studies in Graduate and Postdoctoral Education 9, no. 2 (November 16, 2018): 144–64. http://dx.doi.org/10.1108/sgpe-d-18-00002.
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Purpose This paper aims to examine the use of online social networks by doctoral students. Design/methodology/approach A quantitative online survey was conducted – 448 doctoral students from 15 universities and 11 research institutes in Lithuania were asked about their participation in both academic and non-academic online social networks. Findings The results show that despite efforts to link academics to society, doctoral students are not supported by universities/research institutes nor are doctoral students trained for this purpose, including regarding such threats as offensive posts. Additionally, more comprehensive information is disclosed in academic social networks, but these networks are less common and less frequently used. Research limitations/implications International doctoral students in Lithuania cover about 4.4 per cent of the total population of doctoral students. They were not invited to participate in the survey. Furthermore, doctoral students consider any online social network as their professional (academic) network, as was found from our results. This resulted in the confusion of our definition of academic online social networks. Practical implications Learning about the diverse online roles doctoral students may take could be facilitated were doctoral students to receive clear and consistent awareness-raising and develop self-awareness in the importance of the roles, the most central online social networks and potential threats, and related institutional support to address them. Originality/value This study provides results on how engagement of doctoral students in online social networks might affect their links with society and what academic institutions should promote in doctoral education.
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Yudina, E. N., and I. V. Alekseenko. "Characteristics of Solidarity on Social Networks." Communicology 8, no. 1 (March 31, 2020): 114–27. http://dx.doi.org/10.21453/2311-3065-2020-8-1-114-127.
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The social networking influences all areas of society and stimulates the activity of the social networks communities. Later the importance of social networks revised the researches of the sociological aspects of social solidarity. Solidarity of modern society intensifies according to a sharp increase of possibilities to communicate with the help of the social networks that has become tools of forming the online communities. The authors suggest a new term for characteristics of a new solidarity at network communities – online solidarity. This term shows the connotation with the Internet; it also shows that online solidarity arises on micro level of the interpersonal relations. In the article authors analyze the term and characteristics of online solidarity in network communities and represent the results of the original research (questionnaire, 2019) “Students on Social Networks”. The authors come to conclusion that users with lots of “friends” at social networks feel more successful and socially demanded. Despite of its flexibility and lightness online-solidarity plays an important role in the society and has an influence on the macro level of society.
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Crowne, Kerri Anne, Richard J. Goeke, and Mary Shoemaker. "Enhancing international assignees’ performance with online social networks." Journal of Global Mobility 3, no. 4 (December 14, 2015): 397–417. http://dx.doi.org/10.1108/jgm-09-2014-0045.
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Purpose – Adjustment to the new locale is one of the primary factors that influence performance on an international assignment. The purpose of this paper is to propose a model that depicts how online social networks may contribute to international assignees’ adjustment via their influence on well-being and knowledge transfer. Design/methodology/approach – The present research uses network theory and readily available technology to develop a model of how online supportive social networks and informational social networks may increase the international assignee’s well-being and knowledge transfer (with prior/next assignees and with the organization). These increases will subsequently have a positive impact on the assignee’s adjustment and ultimately his/her job performance. Findings – Since this paper is conceptual rather than empirical, there are no findings; however, it is argued that online social networks may have a positive impact on an expatriate’s well-being, knowledge transfer, adjustment, and job performance. Research limitations/implications – This paper is a conceptual piece, so data will need to be collected to test the model developed here. Furthermore, other factors may influence international assignee adjustment, such as spouse and/or family adjustment. Practical implications – Suggestions are provided regarding how organizations can utilize in-house or external online social networks to assist international assignees. Originality/value – Despite the ubiquity of online social networks, there is a paucity of research examining the potential impact of online social networks on international assignees.
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Gafarov, Fail, Andrey Berdnikov, and Pavel Ustin. "Online social network user performance prediction by graph neural networks." International Journal of Advances in Intelligent Informatics 8, no. 3 (November 30, 2022): 285. http://dx.doi.org/10.26555/ijain.v8i3.859.
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Online social networks provide rich information that characterizes the user’s personality, his interests, hobbies, and reflects his current state. Users of social networks publish photos, posts, videos, audio, etc. every day. Online social networks (OSN) open up a wide range of research opportunities for scientists. Much research conducted in recent years using graph neural networks (GNN) has shown their advantages over conventional deep learning. In particular, the use of graph neural networks for online social network analysis seems to be the most suitable. In this article we studied the use of graph convolutional neural networks with different convolution layers (GCNConv, SAGEConv, GraphConv, GATConv, TransformerConv, GINConv) for predicting the user’s professional success in VKontakte online social network, based on data obtained from his profiles. We have used various parameters obtained from users’ personal pages in VKontakte social network (the number of friends, subscribers, interesting pages, etc.) as their features for determining the professional success, as well as networks (graphs) reflecting connections between users (followers/ friends). In this work we performed graph classification by using graph convolutional neural networks (with different types of convolution layers). The best accuracy of the graph convolutional neural network (0.88) was achieved by using the graph isomorphism network (GIN) layer. The results, obtained in this work, will serve for further studies of social success, based on metrics of personal profiles of OSN users and social graphs using neural network methods.
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Bollen, Johan, Bruno Gonçalves, Guangchen Ruan, and Huina Mao. "Happiness Is Assortative in Online Social Networks." Artificial Life 17, no. 3 (July 2011): 237–51. http://dx.doi.org/10.1162/artl_a_00034.
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Online social networking communities may exhibit highly complex and adaptive collective behaviors. Since emotions play such an important role in human decision making, how online networks modulate human collective mood states has become a matter of considerable interest. In spite of the increasing societal importance of online social networks, it is unknown whether assortative mixing of psychological states takes place in situations where social ties are mediated solely by online networking services in the absence of physical contact. Here, we show that the general happiness, or subjective well-being (SWB), of Twitter users, as measured from a 6-month record of their individual tweets, is indeed assortative across the Twitter social network. Our results imply that online social networks may be equally subject to the social mechanisms that cause assortative mixing in real social networks and that such assortative mixing takes place at the level of SWB. Given the increasing prevalence of online social networks, their propensity to connect users with similar levels of SWB may be an important factor in how positive and negative sentiments are maintained and spread through human society. Future research may focus on how event-specific mood states can propagate and influence user behavior in “real life.”
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Sander, Tom, Ieva Pūķe, and Biruta Sloka. "Revealing Employer’s Name in Social Networks." Economics and Business 30, no. 1 (April 1, 2017): 51–61. http://dx.doi.org/10.1515/eb-2017-0005.
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Abstract The research investigates the question of the importance of mentioning the name of the employer in online and offline social networks. The exchange of information is an important part of social networks and social capital theory. Companies can use the networks of their employees to recruit new hires and to check habits and interests of likely new employees. To do that, the employee has to mention the name of the company in these social networks. The paper compares different real social networks used by family and friends and private and business social network sites (SNSs) as online social networks and compares the differences between men and women. The empirical research has been done by a survey. The survey data are analysed using the main indicators of descriptive statistics, frequency, t-test and cross tables. The results of the research reveal that real social networks are more accepted than virtual social networks. The difference in use of social networks between genders is confirmed.
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Tan, Leonard, Thuan Pham, Kei Ho Hang, and Seng Kok Tan. "Event Prediction in Online Social Networks." Journal of Data Intelligence 2, no. 1 (March 2021): 64–94. http://dx.doi.org/10.26421/jdi2.1-4.
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Event prediction is a very important task in numerous applications of interest like fintech, medical, security, etc. However, event prediction is a highly complex task because it is challenging to classify, contains temporally changing themes of discussion and heavy topic drifts. In this research, we present a novel approach which leverages on the RFT framework developed in \cite{tan2020discovering}. This study addresses the challenge of accurately representing relational features in observed complex social communication behavior for the event prediction task; which recent graph learning methodologies are struggling with. The concept here, is to firstly learn the turbulent patterns of relational state transitions between actors preceeding an event and then secondly, to evolve these profiles temporally, in the event prediction process. The event prediction model which leverages on the RFT framework discovers, identifies and adaptively ranks relational turbulence as likelihood predictions of event occurrences. Extensive experiments on large-scale social datasets across important indicator tests for validation, show that the RFT framework performs comparably better by more than 10\% to HPM \cite{amodeo2011hybrid} and other state-of-the-art baselines in event prediction.
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Vaghefi, Mahyar Sharif, and Derek L. Nazareth. "Mining Online Social Networks: Deriving User Preferences through Node Embedding." Journal of the Association for Information Systems 22, no. 6 (2021): 1625–58. http://dx.doi.org/10.17705/1jais.00711.
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In the last decade, online social networks have become an integral part of life. These networks play an important role in the dissemination of news, individual communication, disclosure of information, and business operations. Understanding the structure and implications of these networks is of great interest to both academia and industry. However, the unstructured nature of the graphs and the complexity of existing network analysis methods limit the effective analysis of these networks, particularly on a large scale. In this research, we propose a simple but effective node embedding method for the analysis of graphs with a focus on its application in online social networks. Our proposed method not only quantifies social graphs in a structured format but also enables user preference identification, community detection, and link prediction in online social networks. We demonstrate the effectiveness of our approach using a network of Twitter users. The results of this research provide valuable insights for marketing professionals seeking to target personalized content and advertising to individual users as well as social network administrators seeking to improve their platform through recommendation systems and the detection of outliers and anomalies.
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Claybaugh, Craig C., and Peter Haried. "Professional Social Network Site Participation." International Journal of Virtual Communities and Social Networking 4, no. 4 (October 2012): 19–32. http://dx.doi.org/10.4018/jvcsn.2012100102.
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Online professional social networks have become a noteworthy tool to help professionals create, strengthen, and maintain valuable business connections. However, the question remains as to who is actually using online professional social networks and how the diffusion of the social network has occurred. Looking at diffusion and usage through innovation diffusion theory, critical mass and a network effects lens, this paper seeks to examine the diffusion of an online professional social network (LinkedIn) for a specific population of university business schools. Using longitudinal analysis (2008 compared to 2011) our findings advocate network dynamics of homogeneous populations display consistent patterns of participation and non-participation. The authors’ findings suggest LinkedIn diffusion is not consistent across all business schools examined. A greater critical mass and network effect appears to have been achieved across larger research universities when compared to smaller university populations. An analysis of the results and future research directions are presented.
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Cobb, Nathan K., Amanda L. Graham, M. Justin Byron, Raymond S. Niaura, and David B. Abrams. "Online Social Networks and Smoking Cessation: A Scientific Research Agenda." Journal of Medical Internet Research 13, no. 4 (December 19, 2011): e119. http://dx.doi.org/10.2196/jmir.1911.
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Sufa, Siska Armawati, Andry Alamsyah, Suwandi Sumartias, Feliza Zubair, and Susie Perbawasari. "Twitter and Online Prostitution: The Communication Network of Online Prostitution in Twitter." Webology 19, no. 1 (January 20, 2022): 2797–810. http://dx.doi.org/10.14704/web/v19i1/web19186.
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The information developments and communication technology also has a negative side. This study is aimed to determine the online prostitution communication network on Twitter and understanding of online prostitution on Twitter. This study uses SNA (Social Network Analysis). SNA views social relations as a theory of networks consisting of nodes and relationships (also called edges, links, or connections). Nodes are individual actors in the network and the relationships are between actors. The data set used in this study is tweet data from Twitter, with the keyword samples being “openBO”. The hashtags were chosen because they are the most widely used the hashtags for online prostitution. The data is taken with a period between January 2020 to December 2020. The data is taken and processed using NodeXL Basic, one of the plugins for Microsoft Excel that can be used to process data from social networks. This research found there are 3,673 nodes and 54,969 edges. The hashtags utilization is usually utilized by online whores to advance their administrations. A few prostitutes are independent, it is implying that they don’t connect with others in advancing business sex administrations. It is not reliant upon pimps since pimps mean to lessen their business chain.
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Alam, Syed Shah, Chieh-Yu Lin, Mohd Helmi Ali, Nor Asiah Omar, and Mohammad Masukujjaman. "Working Adults' Buying Intention Through Online Social Network." International Journal of Technology and Human Interaction 17, no. 4 (October 2021): 92–116. http://dx.doi.org/10.4018/ijthi.2021100106.
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Most businesses have online social media presence; therefore, understanding of working adult's perception on buying through online social networks is vital. The aim of this study is to examine the effect of perceived value, sociability, usability, perceived risk, trust, and e-word-of-mouth on buying intention through online social network sites. The research model for this study was developed based on the literature on information system research. This study adopted convenient sampling of non-probability sampling procedure. Data were collected through self-administered questionnaire, and PLS-based path analysis was used to analyse responses. The findings of the study shows that perceived value, sociability, usability, e-word-of-mouth, attitude, and subjective norm are significant constructs of buying intention through online social networks. This research can serve as a starting point for online shopping research through online social media while encouraging further exploration and integration addition adoption constructs.
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Alemerien, Khalid. "Usable Security and Privacy on Online Social Networks." International Journal of Software Innovation 9, no. 2 (April 2021): 35–68. http://dx.doi.org/10.4018/ijsi.2021040103.
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Hundreds of millions of people use online social networks (OSNs), and this use is growing rapidly. On the one hand, users of OSNs have created accounts, which include their personal information, interests, associations, postings, daily activities, sharing of social media, and so forth. In addition, users want to protect these information and activities. But on the other hand, they want to use the services, which are provided by OSNs in order to stay in touch with others. Therefore, for achieving this desire, users reveal their personal information intentionally or accidentally. Why? Because users of OSNs do not have adequate information that helps them in making security and privacy decisions effectively in addition to inadequate feedback about the implications of user decisions. This means users do not know what to reveal and how. In order to cope with this problem, a systematic literature review of the usable security and privacy on OSNs was performed. This review is an attempt to pursue the contours of research in OSNs. Therefore, this paper discusses the existing research work, highlights the main research challenges and existing solutions, identifies open research issues, and proposes some directions for future research in the usable security and privacy on OSNs.
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Gürsakal, Necmi, and Aras Bozkurt. "Identifying gatekeepers in online learning networks." World Journal on Educational Technology: Current Issues 9, no. 2 (April 11, 2017): 75. http://dx.doi.org/10.18844/wjet.v9i2.1277.
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The rise of the networked society has not only changed our perceptions but also the definitions, roles, processes and dynamics of online learning networks. From offline to online worlds, networks are everywhere and gatekeepers are an important entity in these networks. In this context, the purpose of this paper is to explore gatekeeping and gatekeepers in online learning networks. In this regard, it will examine the indicators of gatekeeping and gatekeepers, and gatekeepers’ roles and functions in learning network formation processes. For the purposes of the research, the paper uses multiple-case design and examines three connectivist Massive Open Online Courses through social network analysis. The findings of the research indicate that betweenness centrality is an important indicator of gatekeeping and gatekeepers. Moreover, gatekeepers have an important role in learning network formation processes and their actions are one of the determiners of the network structure.
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Ariel, Yaron, Vered Elishar-Malka, Dana Weimann-Saks, and Ruth Avidar. "Online agenda-setting research." Agenda Setting Journal 1, no. 2 (August 18, 2017): 117–36. http://dx.doi.org/10.1075/asj.1.2.03ari.
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Abstract Agenda-setting research has been performed for more than four decades, both in traditional and online media, and the tools employed for this task have been very much accepted by media researchers around the world. Nevertheless, analysis of the public agenda in new media, particularly across social networks, requires re-thinking these same tools, which creates a series of methodological and theoretical challenges. The present paper seeks to illuminate these challenges and propose possible solutions for some of them.
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Zhang, Jingwen, and Damon Centola. "Social Networks and Health: New Developments in Diffusion, Online and Offline." Annual Review of Sociology 45, no. 1 (July 30, 2019): 91–109. http://dx.doi.org/10.1146/annurev-soc-073117-041421.
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The relationship between social networks and health encompasses everything from the flow of pathogens and information to the diffusion of beliefs and behaviors. This review addresses the vast and multidisciplinary literature that studies social networks as a structural determinant of health. In particular, we report on the current state of knowledge on how social contagion dynamics influence individual and collective health outcomes. We pay specific attention to research that leverages large-scale online data and social network experiments to empirically identify three broad classes of contagion processes: pathogenic diffusion, informational and belief diffusion, and behavioral diffusion. We conclude by identifying the need for more research on ( a) how multiple contagions interact within the same social network, ( b) how online social networks impact offline health, and ( c) the effectiveness of social network interventions for improving population health.
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Claybaugh, Craig C., and Peter Haried. "Professional Social Network Participation of Business School Graduates." International Journal of Information Systems and Social Change 5, no. 1 (January 2014): 1–15. http://dx.doi.org/10.4018/ijissc.2014010101.
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Social networks are having a profound impact on how professionals communicate and connect with each other. Online professional social networks have become a significant resource for building and maintaining invaluable business connections. Recent university graduates are a particular population often in search of building social networks to further professional development. Participation in online social networks provides a valuable tool for recent university graduates to create and sustain their professional connections and business relationships. This paper seeks to gain a better understanding of the effect university (nationally ranked, large urban, and regional), gender and degree type (undergraduate and graduate) has on online professional social network participation. The authors' business school college graduate findings suggest that university, degree type, and gender were associated with the likelihood of joining the online professional social network LinkedIn. An analysis of the results and future research directions are presented.
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McNutt, Kathleen. "Research Note: Do Virtual Policy Networks Matter? Tracing Network Structure Online." Canadian Journal of Political Science 39, no. 2 (June 2006): 391–405. http://dx.doi.org/10.1017/s0008423906060161.
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Abstract.The Internet, operating as a technologically embedded laboratory of human activity, provides social scientists with a new set of analytical tools by which to test and replicate models of social and political behaviour, with data extrapolated from the regularities of online activity, organization and information exchange. This research note demonstrates that virtual policy networks, arrangements of public interaction between mutually supporting actors that form around policy activities, exist on the Web. In addition, the note considers whether or not Canadian virtual policy networks are mimicking their respective national policy communities through the application of a methodological approach referred to as link structure analysis. Four sectorally based networks, including Aboriginal policy, agriculture, banking and women-centred policy, are analyzed to assess the extent of virtual policy networks' replication of real world policy dynamics.Résumé.L'Internet, agissant comme laboratoire technologique de l'activité humaine, fournit aux chercheurs un nouvel ensemble d'outils analytiques par lesquels ils peuvent tester et recréer des modèles de comportements sociaux et politiques, à l'aide de données extrapolées à partir d'activités, d'organisations et d'échanges d'information en ligne. Cet essai montre qu'il existe sur Internet des réseaux virtuels d'action politique, à savoir des arrangements d'interaction publique entre différents acteurs sociaux se regroupant autour de certaines idées politiques. En outre, il essaie de déterminer si les réseaux virtuels canadiens imitent leurs communautés politiques nationales respectives, en utilisant une approche méthodologique désignée sous le nom d'analyse de la structure des liens. Quatre réseaux appartenant à des secteurs distincts, soit la politique autochtone, l'agriculture, les opérations bancaires et la condition féminine, sont analysés pour évaluer l'ampleur de la reproduction des dynamiques politiques et sociales du monde réel par les réseaux d'action politique virtuels.
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Fuentes Cancell, Dieter Reynaldo, Odiel Estrada Molina, and Nilda Delgado Yanes. "Las redes sociales digitales: una valoración socioeducativa. Revisión sistemática." Revista Fuentes 1, no. 23 (2021): 41–52. http://dx.doi.org/10.12795/revistafuentes.2021.v23.i1.11947.
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The future and already current industrial revolution 4.0 demand the introduction of a digital transformation in the higher education contributing to the formation of competent professionals, for which, they are evidenced in the pedagogies and emergent technologies, an increase of didactic experiences in the use of the digital social networks. In this research a systematic review to identify current trends in the use of online social networks for educational purposes are performed. PRISMA protocol was used and analyzed 79 studies present in the database Scopus. In the systematic review, the following questions are answered: What types of designs predominate in the scientific literature? What is the dependentindependent pairs of variables? And What are the current trends in the use of digital social networks for educational purposes? As a result of this research, Facebook is reaffirmed as the social network most used by educators and the need for the integrated and varied use of these networks. It concludes with the defense of the following trends: university institutional communication policies from the curricular levels; the development of creativity, cultural convergence and media diversification; educational innovation; media culture and academic digital identity
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Yu, Liguo, and Yingmei Li. "An Empirical Study of Virtual Social Networks." International Journal of Social Media and Online Communities 13, no. 2 (July 2021): 1–21. http://dx.doi.org/10.4018/ijsmoc.2021070101.
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Virtual social network is a kind of social network established through indirect interactions between individuals, especially through online interactions. Virtual social network has significant implications on business operations, governing, scientific research, and social relations. This paper describes several virtual social networks and studies their properties and effects using empirical approach and computer simulations. Furthermore, the authors find that these virtual social networks have similar distributions with respect to the frequency of nodes and different edges. These distributions are similar between directed networks and undirected networks. In addition, through simulations they demonstrate that the roles played by different nodes in a virtual social network are unequal. Limitations of this study and future research directions are also presented.
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Zhang, Lin, and Kan Li. "Influence Maximization Based on Snapshot Prediction in Dynamic Online Social Networks." Mathematics 10, no. 8 (April 18, 2022): 1341. http://dx.doi.org/10.3390/math10081341.
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With the vigorous development of the mobile Internet, online social networks have greatly changed the way of life of human beings. As an important branch of online social network research, influence maximization refers to finding K nodes in the network to form the most influential seed set, which is an abstract model of viral marketing. Most of the current research is based on static network structures, ignoring the important feature of network structures changing with time, which discounts the effect of seed nodes in dynamic online social networks. To address this problem in dynamic online social networks, we propose a novel framework called Influence Maximization based on Prediction and Replacement (IMPR). This framework first uses historical network snapshot information to predict the upcoming network snapshot and then mines seed nodes suitable for the dynamic network based on the predicted result. To improve the computational efficiency, the framework also adopts a fast replacement algorithm to solve the seed nodes between different snapshots. The scheme we adopted exhibits four advantages. First, we extended the classic influence maximization problem to dynamic online social networks and give a formal definition of the problem. Second, a new framework was proposed for this problem and a proof of the solution is given in theory. Third, other classical algorithms for influence maximization can be embedded into our framework to improve accuracy. More importantly, to reveal the performance of the scheme, a series of experiments based on different settings on real dynamic online social network datasets were carried out, and the experimental results are very promising.
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Cordero-Gutiérrez, Rebeca, and Libia Santos-Requejo. "Intention to participate in online commercial experiments by social network’s users." Management Research Review 39, no. 4 (April 18, 2016): 378–98. http://dx.doi.org/10.1108/mrr-06-2014-0128.
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Purpose The purpose of this paper is to analyze the underlying differences in the intention to participate in online commercial experiments through the social network considering users’ gender and age. Design/methodology/approach The model of this paper uses two relevant variables, trust and attitude, to test the behavioral intention. There were 269 data sets from social network’s users. Factorial analysis and linear regression were used in the analysis of the data obtained to investigate the differences in gender and age in the intention to participate in online commercial experiments. Findings The results of this paper show that there exist differences among women and men, and among youthers and adults. Women and youthers are the most desirable groups to conduct commercial experiments through social networks. Research limitations/implications From the point of view of the academics, this paper increases the knowledge of social network’s possibilities as a marketing tool. Practical implications This study and its conclusions are relevant for entrepreneurs in any field who want to reach their customers through a horizontal social network because they can improve the online experiments’ profit. Entrepreneurs can know and understand their customers better, taking into account their wishes, tastes and interests through when participating in a commercial experiment. Originality/value This paper describes the possibilities that social networks like Facebook offer entrepreneurs to know the intention of users to participate in an online commercial experiment. Moreover, the differences in gender and age allow in adapting the contents of the online commercial experiments to get better results. In addition, this research contributes to the investigation in the possibilities of social networks as marketing tools.
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Ai, Chuan, Bin Chen, Hailiang Chen, Weihui Dai, and Xiaogang Qiu. "Geographical Structural Features of the WeChat Social Networks." ISPRS International Journal of Geo-Information 9, no. 5 (May 1, 2020): 290. http://dx.doi.org/10.3390/ijgi9050290.
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Recently, spatial interaction analysis of online social networks has become a big concern. Early studies of geographical characteristics analysis and community detection in online social networks have shown that nodes within the same community might gather together geographically. However, the method of community detection is based on the idea that there are more links within the community than that connect nodes in different communities, and there is no analysis to explain the phenomenon. The statistical models for network analysis usually investigate the characteristics of a network based on the probability theory. This paper analyzes a series of statistical models and selects the MDND model to classify links and nodes in social networks. The model can achieve the same performance as the community detection algorithm when analyzing the structure in the online social network. The construction assumption of the model explains the reasons for the geographically aggregating of nodes in the same community to a degree. The research provides new ideas and methods for nodes classification and geographic characteristics analysis of online social networks and mobile communication networks and makes up for the shortcomings of community detection methods that do not explain the principle of network generation. A natural progression of this work is to geographically analyze the characteristics of social networks and provide assistance for advertising delivery and Internet management.
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Boroon, Layla, Babak Abedin, and Eila Erfani. "The Dark Side of Using Online Social Networks." Journal of Global Information Management 29, no. 6 (November 2021): 1–21. http://dx.doi.org/10.4018/jgim.20211101.oa34.
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Research on online social networks (OSNs) has focused overwhelmingly on their benefits and potential, with their negative effects overlooked. This study builds on the limited existing work on the so-called ‘dark side’ of using OSNs. The authors conducted a systematic review of selected databases and identified 46 negative effects of using OSNs from the users’ perspective, which is a rich spectrum of users’ negative experiences. This article then proposed nomenclature and taxonomy for the dark side of using OSNs by grouping these negative effects into six themes: cost of social exchange, cyberbullying, low performance, annoying content, privacy concerns and security threats. This study then conducted structured interviews with experts to confirm the sense-making and validity of the proposed taxonomy. This study discusses the confirmed taxonomy and outlines directions for future research.
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Li, Pei, Yini Zhang, Fengcai Qiao, and Hui Wang. "Information diffusion in structured online social networks." Modern Physics Letters B 29, no. 13 (May 18, 2015): 1550063. http://dx.doi.org/10.1142/s0217984915500633.
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Nowadays, due to the word-of-mouth effect, online social networks have been considered to be efficient approaches to conduct viral marketing, which makes it of great importance to understand the diffusion dynamics in online social networks. However, most research on diffusion dynamics in epidemiology and existing social networks cannot be applied directly to characterize online social networks. In this paper, we propose models to characterize the information diffusion in structured online social networks with push-based forwarding mechanism. We introduce the term user influence to characterize the average number of times that messages are browsed which is incurred by a given type user generating a message, and study the diffusion threshold, above which the user influence of generating a message will approach infinity. We conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of use in understanding the diffusion dynamics in online social networks and also critical for advertisers in viral marketing who want to estimate the user influence before posting an advertisement.
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Li, Xuefeng, Yixian Yang, Yuling Chen, and Xinxin Niu. "A Privacy Measurement Framework for Multiple Online Social Networks against Social Identity Linkage." Applied Sciences 8, no. 10 (October 1, 2018): 1790. http://dx.doi.org/10.3390/app8101790.
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Recently, the number of people who are members of multiple online social networks simultaneously has increased. However, if these people share everything with others, they risk their privacy. Users may be unaware of the privacy risks involved with sharing their sensitive information on a network. Currently, there are many research efforts focused on social identity linkage (SIL) on multiple online social networks for commercial services, which exacerbates privacy issues. Many existing studies consider methods of encrypting or deleting sensitive information without considering if this is unreasonable for social networks. Meanwhile, these studies ignore privacy awareness, which is rudimentary and critical. To enhance privacy awareness, we discuss a user privacy exposure measure for users who are members of multiple online social networks. With this measure, users can be aware of the state of their privacy and their position on a privacy measurement scale. Additionally, we propose a straightforward method through our framework to reduce information loss and foster user privacy awareness by using spurious content for required fields.
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Vaish, Abhishek, Rajiv Krishna G., Akshay Saxena, Dharmaprakash M., and Utkarsh Goel. "Quantifying Virality of Information in Online Social Networks." International Journal of Virtual Communities and Social Networking 4, no. 1 (January 2012): 32–45. http://dx.doi.org/10.4018/jvcsn.2012010103.
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The aim of this research is to propose a model through which the viral nature of an information item in an online social network can be quantified. Further, the authors propose an alternate technique for information asset valuation by accommodating virality in it which not only complements the existing valuation system, but also improves the accuracy of the results. They use a popularly available YouTube dataset to collect attributes and measure critical factors such as share-count, appreciation, user rating, controversiality, and comment rate. These variables are used with a proposed formula to obtain viral index of each video on a given date. The authors then identify a conventional and a hybrid asset valuation technique to demonstrate how virality can fit in to provide accurate results.The research demonstrates the dependency of virality on critical social network factors. With the help of a second dataset acquired, the authors determine the pattern virality of an information item takes over time.
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Ma, Li Juan. "Research on the Development and Influence of the Cyberculture." Advanced Materials Research 1030-1032 (September 2014): 2753–56. http://dx.doi.org/10.4028/www.scientific.net/amr.1030-1032.2753.
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Cyberculture or computer culture is the culture that has emerged, or is emerging, from the use of computer networks for communication, entertainment, and business. It is also the study of various social phenomena associated with the Internet and other new forms of the network communication, such as online communities, online multi-player gaming, wearable computing, social gaming, social media, mobile apps, augmented reality, and texting, and includes issues related to identity, privacy, and network formation. With the era of cyberculture, ideological issues are prominent increasingly at all levels of society in cyberculture.
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Li, Zhepeng, Xiao Fang, Xue Bai, and Olivia R. Liu Sheng. "Utility-Based Link Recommendation for Online Social Networks." Management Science 63, no. 6 (June 2017): 1938–52. http://dx.doi.org/10.1287/mnsc.2016.2446.
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Han, Shuhe. "Research on Online Social Network Information Leakage-Tracking Algorithm Based on Deep Learning." Computational Intelligence and Neuroscience 2022 (June 28, 2022): 1–11. http://dx.doi.org/10.1155/2022/1926794.
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The rapid iteration of information technology makes the development of online social networks increasingly rapid, and its corresponding network scale is also increasingly large and complex. The corresponding algorithms to deal with social networks and their corresponding related problems are also increasing. The corresponding privacy protection algorithms such as encryption algorithm, access control strategy algorithm, and differential privacy protection algorithm have been studied and analyzed, but these algorithms do not completely solve the problem of privacy disclosure. Based on this, this article first searches and accurately filters the relevant information and content of online social networks based on the deep convolution neural network algorithm, so as to realize the perception and protection of users’ safe content. For the corresponding graphics and data, this article introduces the compressed sensing technology to randomly disturb the corresponding graphics and data. At the level of tracking network information leakage algorithm, this article proposes a network information leakage-tracking algorithm based on digital fingerprint, which mainly uses relevant plug-ins to realize the unique identification processing of users, uses the uniqueness of digital fingerprint to realize the tracking processing of leakers, and formulates the corresponding coding scheme based on the social network topology, and at the same time, the network information leakage-tracking algorithm proposed in this article also has high efficiency in the corresponding digital coding efficiency and scalability. In order to verify the advantages of the online social network information leakage-tracking algorithm based on deep learning, this article compares it with the traditional algorithm. In the experimental part, this article mainly compares the accuracy index, recall index, and performance index. At the corresponding accuracy index level, it can be seen that the maximum improvement of the algorithm proposed in this article is about 10% compared with the traditional algorithm. At the corresponding recall index level, the proposed algorithm is about 5–8% higher than the traditional algorithm. Corresponding to the overall performance index, it improves the performance by about 50% compared with the traditional algorithm. The comparison results show that the proposed algorithm has higher accuracy and the corresponding source tracking is more accurate.
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Ryan, Gemma Sinead. "Online social networks for patient involvement and recruitment in clinical research." Nurse Researcher 21, no. 1 (September 2013): 35–39. http://dx.doi.org/10.7748/nr2013.09.21.1.35.e302.
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Oseni, Kazeem Oluwakemi, Kate Dingley, and Penny Hart. "Instant Messaging and Social Networks — The Advantages in Online Research Methodology." International Journal of Information and Education Technology 8, no. 1 (2018): 56–62. http://dx.doi.org/10.18178/ijiet.2018.8.1.1012.
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Madro, Marek. "Possibilities of Psychological Intervention on Social Networks." Acta Educationis Generalis 8, no. 3 (December 1, 2018): 35–49. http://dx.doi.org/10.2478/atd-2018-0016.
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AbstractIntroduction: Nowadays we are looking for help and answers to our questions more and more often on the Internet. People use social networks to search for communities or groups whose members experience similar difficulties. These are often online groups that focus on psychological problems, domestic violence, etc. Members receive instant feedback and at the same time, due to the online disinhibition effect, they do not feel the fear, shame or worries they would feel in personal contact (Griffiths, 2005). The content of such self-help groups is not always helpful, but may rather induce pathological behaviour. However, the group administrator can influence the atmosphere in the group and its content itself (Niwa & Mandrusiak, 2012).Purpose: The purpose of this research was to find a space to perform professional psychological interventions inside online self-help groups on social networks. The concept of a field worker was used in this research. The field worker offers helping services to clients in an environment natural to them and where the worker can provide the client with emergency help during the crisis and prevent other clients from offering risk advices (Ambrózová, Vitálošová, & Labáth, 2006).Methods: We have conducted qualitative research using the method of content-frequency analysis. The sample for this study consisted of 10 closed online self-help groups focusing on topics such as depression, anxiety disorder, domestic violence, self-injurious and suicidal thoughts and tendencies, etc. For the purpose of this research we created an online group moderated by professionals, focusing on similar topics of mental disorders.Conclusions: The research results indicated that group members exchanged useful information (35.43%), described their current difficulties they were experiencing (32.33%), shared their own experiences (10.53%), and also published information on what had helped them manage the difficult feelings and situations they had been experiencing (6.39%). However, we also identified risky statements and threatening recommendations in posts and comments. Based on the results, we outlined the possibilities of online field worker interventions and described techniques of interventions that the professional can use for the benefit of group members.
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Nguyen, Thanh Duy, Nghia Dinh Tran, and Cuong Manh Pham. "Proposing the online advertising on social network adoption model in Vietnam." Science and Technology Development Journal 16, no. 3 (September 30, 2013): 5–19. http://dx.doi.org/10.32508/stdj.v16i3.1626.
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Social network is strongly growing and is increasingly becoming an integral part of the daily life of people in all over the world; online advertising on social networks is a potential market for the business towards. With the booming development of web 2.0, online advertising is showing a remarkable transformation, Vietnam marketers are approaching the new form of online advertising on social network such as facebook, zingme, google+, linkedin, twitter, yume... The studies showed that the popularity of online advertising on social networking is essential. This study proposes a new model that is online advertising on social network adoption model in Vietnam. Research results shows that independent factors affect to attitude toward advertising and attitude toward advertising affects to online advertising on social networks; all proposed hypotheses are accepted. The model explains 72.9% of variance in the online advertising on social network adoption.
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Lemay, David, Tenzin Doleck, and Christopher Brinton. "SLOAN: Social Learning Optimization Analysis of Networks." International Review of Research in Open and Distributed Learning 23, no. 4 (November 1, 2022): 93–122. http://dx.doi.org/10.19173/irrodl.v23i4.6484.
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Online discussion research has mainly been conducted using case methods. This article proposes a method for comparative analysis based on network metrics such as information entropy and global network efficiency as more holistic measures characterizing social learning group dynamics. We applied social learning optimization analysis of networks (SLOAN) to a data set consisting of Coursera courses from a range of disciplines. We examined the relationship of discussion forum uses and measures of network efficiency, characterized by the information flow through the network. Discussion forums vary greatly in size and in use. Courses with a greater prevalence of subject-related versus procedural talk differed significantly in seeking but not disseminating behaviors in massive open online course discussion forums. Subject-related talk was related to higher network efficiency and had higher seeking and disseminating scores overall. We discuss the value of SLOAN for social learning and argue for the experimental study of online discussion optimization using a discussion post recommendation system for maximizing social learning.
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Mican, Daniel, Dan-Andrei Sitar-Tăut, and Ioana-Sorina Mihuţ. "User Behavior on Online Social Networks: Relationships among Social Activities and Satisfaction." Symmetry 12, no. 10 (October 10, 2020): 1656. http://dx.doi.org/10.3390/sym12101656.
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Social networking sites (SNSs) are now ubiquitous communities for constant online interpersonal interactions that trigger symmetric or asymmetric effects on our everyday life. Recent studies advocate in favor of the significant role that SNSs have in promoting well-being and, more importantly, in disseminating reliable information during a global crisis, such as the current COVID-19 pandemic. Based on the growing importance of SNSs to the global framework, the main purpose of this study is to empirically assess the link between the use of symmetric social networks such as Facebook, or asymmetric social networks, like Instagram, and the level of satisfaction, employing the methodology of structural equation modeling. The results of the research validate the hypothesis that SNS activities increase the level of satisfaction, and therefore, that there is a direct link between the number of posts and comments and the level of satisfaction. Furthermore, based on the reversible and significant link between the level of satisfaction and the importance attributed to SNSs, the main conclusion of the study is that the higher the importance of the SNS, the greater the level of dissatisfaction experienced by users. Also, public activities on social networks positively affect social network satisfaction, while private activities have a direct negative relationship with the importance of social networks.
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van Woudenberg, T. J., K. E. Bevelander, W. J. Burk, C. R. Smit, L. Buijs, and M. Buijzen. "Comparing the measurement of different social networks: Peer nominations, online communication, and proximity data." Network Science 8, no. 1 (January 31, 2020): 62–78. http://dx.doi.org/10.1017/nws.2019.65.
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AbstractBackground:Technological progress has enabled researchers to use new unobtrusive measures of relationships between actors in social network analysis. However, research on how these unobtrusive measures of peer connections relate to traditional sociometric nominations in adolescents is scarce. Therefore, the current study compared traditional peer nominated networks with more unobtrusive measures of peer connections: Communication networks that consist of instant messages in an online social platform and proximity networks based on smartphones’ Bluetooth signals that measure peer proximity. The three social network types were compared in their coverage, stability, overlap, and the extent to which the networks exhibit the often observed sex segregation in adolescent social networks.Method:Two samples were derived from the MyMovez project: a longitudinal sample of 444 adolescents who participated in the first three waves of the first year of the project (Y1; 51% male; Mage = 11.29, SDage = 1.26) and a cross-sectional sample of 774 adolescents that participated in fifth wave in the third year (Y3; 48% male; Mage = 10.76, SDage = 1.23). In the project, all participants received a research smartphone and a wrist-worn accelerometer. On the research smartphone, participants received daily questionnaires such as peer nomination questions (i.e., nominated network). In addition, the smartphone automatically scanned for other smartphones via Bluetooth signal every 15 minutes of the day (i.e., proximity network). In the Y3 sample, the research smartphone also had a social platform in which participants could send messages to each other (i.e., communication network).Results:The results show that nominated networks provided data for the most participants compared to the other two networks, but in these networks, participants had the lowest number of connections with peers. Nominated networks showed to be more stable over time compared to proximity or communication networks. That is, more connections remained the same in nominated networks than in proximity networks over the three waves of Y1. The overlap between the three networks was rather small, indicating that the networks measured different types of connections. Nominated and communication networks were segregated by sex, whereas this was less the case in proximity networks.Conclusion:The communication and proximity networks seem to be promising unobtrusive measures of peer connections and are less of a burden to the participant compared to a nominated network. However, given the structural differences between the networks and the number of connections per wave, the communication and proximity networks should not be used as direct substitutes for sociometric nominations, and researchers should bear in mind what type of connections they wish to assess.
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García-Galera, Mª-Carmen, Mercedes del-Hoyo-Hurtado, and Cristóbal Fernández-Muñoz. "Engaged youth in Internet. The role of social networks in social active participation." Comunicar 22, no. 43 (July 1, 2014): 35–43. http://dx.doi.org/10.3916/c43-2014-03.
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This paper contributes to the analysis of the role that social networks play in civic, social mobilization and solidarity of Spanish young people, considering whether social networks are responsible for active social commitment off-line or if they just intensify an existing or previous tendency towards social participation. This research was undertaken by on-line questionnaire –Likert scale and multiple choice questions– in collaboration with the Spanish social network Tuenti where more than 1,300 young people took part. The results show significant percentages of participation exclusively on-line although there were more than 80% of young people, in a way or another, involved in actions to which they were called by social networks. The study analyzes the forms of participation in solidarity actions and the influence of factors such as geographical, social or emotional proximity to causes on the degree of participation on-line and off-line. The article shows that social networks have changed the meaning of participation. They are encouraging young people not mobilized away from social networks, to take action, so it proposes in its conclusions the need to overcome the dichotomy that opposes on-line and off-line activism and passivity. Este trabajo analiza el papel que las redes sociales juegan en la movilización ciudadana, social y solidaria de los jóvenes españoles. El objetivo es observar si son responsables de que los jóvenes activos online demuestren también su compromiso en la vida fuera de la Red, y si su predisposición existente o no hacia la participación, se intensifica a través de estas redes sociales y en su respuesta offline. Para ello se desarrolló una investigación online a través de cuestionario –con preguntas en Escala de Likert y de elección múltiple– en colaboración con la red social Tuenti en la que participaron más de 1.300 jóvenes. Los resultados ponen de manifiesto porcentajes significativos de participación solidaria exclusivamente online, si bien se observa que más del 80% de los jóvenes, de una u otra forma, participan en las acciones a las que se les convoca a través de redes sociales. El estudio examina también las formas de participación en acciones solidarias y la influencia de factores como la proximidad geográfica, social o emocional sobre la participación online y offline. Las redes sociales han cambiado el significado de la participación, están incentivando el compromiso y consiguiendo que jóvenes que no se movilizaban fuera de ellas, pasen a la acción. Por ello propone entre sus conclusiones, la necesidad de superar la dicotomía que opone online y offline en el ámbito de la participación social.
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Le, Van-Vang, Phuong Nguyen Huy Pham, Tran Kim Toai, and Vaclav Snasel. "An approach of anchor link prediction using graph attention mechanism." Bulletin of Electrical Engineering and Informatics 11, no. 5 (October 1, 2022): 2895–902. http://dx.doi.org/10.11591/eei.v11i5.4274.
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Nowadays social networks such as Twitter, LinkedIn, and Facebook are a popular and necessary platform. It is considered a miniature of an actual social network because of its advantages in connecting and sharing information between users. The analysis of data on online social networks has become a field that has attracted a lot of attention from the research community and anchor link prediction is one of the main research directions in this field. Depending on demand, a user can simultaneously participate in many different online social networks, anchor link prediction is a kind of task that determines the identity of a user on many different social networks. In this article, we proposed an algorithm that determines missing/future anchor links between users from two different online social networks. Our algorithm utilizes the graph attention technique to represent the source and target network into the low-dimension embedding spaces, we then apply the canonical correlation analysis to recline their embeddings into same latent spaces for final prediction.
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Khandare, Miss Komal K. "Various Privacy and Security Issues in Online Social Networks." International Journal for Research in Applied Science and Engineering Technology 9, no. 12 (December 31, 2021): 142–46. http://dx.doi.org/10.22214/ijraset.2021.39203.
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Abstract: Social networks have become a part of human life. online interaction, communication, and interest sharing, letting individuals create online profiles that other users can view these are basic features that are offer by most of social networking sites Unfortunately, In many cases, users are not even aware of the disclosure of their personal information through their profiles. Leakage of a user’s private information can happen in different ways. Many of the security risks associated with using social media are presented in this paper. Also, the issue of privacy and how it relates to security are described. Based on these discussions, some key points are provided to improve a user’s privacy and security on social networks. Our inquest will help the readers to understand the security and privacy issues for the social network users, and this research will help the user. Keywords: OSN; security; classic privacy threats; modern threat.
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Hutton, Luke, and Tristan Henderson. "Toward Reproducibility in Online Social Network Research." IEEE Transactions on Emerging Topics in Computing 6, no. 1 (January 2018): 156–67. http://dx.doi.org/10.1109/tetc.2015.2458574.
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Dimitrova, Dimitrina, and Emmanuel Koku. "Managing Collaborative Research Networks." International Journal of Virtual Communities and Social Networking 2, no. 4 (October 2010): 1–22. http://dx.doi.org/10.4018/jvcsn.2010100101.
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This paper explores how management practices shape the way dispersed communities of practice (CoPs) function. The analysis is a case study of a dispersed community engaged in conducting and managing collaborative research. The analysis uses data from a social network survey and semi-structured interviews to capture the management practices in the community and demonstrate how they are linked to the patterns of information flows and communication.This analysis is a test case for the broader issue of how distributed communities function. It shows that even highly distributed CoPs may have a dual life: they exist both online and offline, in both face-to-face meetings and email exchanges of their participants. The study examines a dispersed community engaged in conducting and managing collaborative research. The analysis uses data from a social network survey and interviews to examine its managerial practices, information exchanges and communication practices.
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Lu, Yingjie, Shuwen Luo, and Xuan Liu. "Development of Social Support Networks by Patients With Depression Through Online Health Communities: Social Network Analysis." JMIR Medical Informatics 9, no. 1 (January 7, 2021): e24618. http://dx.doi.org/10.2196/24618.
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Background In recent years, people with mental health problems are increasingly using online social networks to receive social support. For example, in online depression communities, patients can share their experiences, exchange valuable information, and receive emotional support to help them cope with their disease. Therefore, it is critical to understand how patients with depression develop online social support networks to exchange informational and emotional support. Objective Our aim in this study was to investigate which user attributes have significant effects on the formation of informational and emotional support networks in online depression communities and to further examine whether there is an association between the two social networks. Methods We used social network theory and constructed exponential random graph models to help understand the informational and emotional support networks in online depression communities. A total of 74,986 original posts were retrieved from 1077 members in an online depression community in China from April 2003 to September 2017 and the available data were extracted. An informational support network of 1077 participant nodes and 6557 arcs and an emotional support network of 1077 participant nodes and 6430 arcs were constructed to examine the endogenous (purely structural) effects and exogenous (actor-relation) effects on each support network separately, as well as the cross-network effects between the two networks. Results We found significant effects of two important structural features, reciprocity and transitivity, on the formation of both the informational support network (r=3.6247, P<.001, and r=1.6232, P<.001, respectively) and the emotional support network (r=4.4111, P<.001, and r=0.0177, P<.001, respectively). The results also showed significant effects of some individual factors on the formation of the two networks. No significant effects of homophily were found for gender (r=0.0783, P=.20, and r=0.1122, P=.25, respectively) in the informational or emotional support networks. There was no tendency for users who had great influence (r=0.3253, P=.05) or wrote more posts (r=0.3896, P=.07) or newcomers (r=–0.0452, P=.66) to form informational support ties more easily. However, users who spent more time online (r=0.6680, P<.001) or provided more replies to other posts (r=0.5026, P<.001) were more likely to form informational support ties. Users who had a big influence (r=0.8325, P<.001), spent more time online (r=0.5839, P<.001), wrote more posts (r=2.4025, P<.001), or provided more replies to other posts (r=0.2259, P<.001) were more likely to form emotional support ties, and newcomers (r=–0.4224, P<.001) were less likely than old-timers to receive emotional support. In addition, we found that there was a significant entrainment effect (r=0.7834, P<.001) and a nonsignificant exchange effect (r=–0.2757, P=.32) between the two networks. Conclusions This study makes several important theoretical contributions to the research on online depression communities and has important practical implications for the managers of online depression communities and the users involved in these communities.
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Lee, Seungyoon. "Editorial: Networks and Organizing Processes in Online Social Media." Media and Communication 10, no. 2 (April 29, 2022): 1–4. http://dx.doi.org/10.17645/mac.v10i2.5616.
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Online social media present unprecedented opportunities and challenges for a range of organizing processes such as information sharing, knowledge creation, collective action, and post-disaster resource mobilization. Concepts and tools of network research can help highlight key aspects of online interaction. This editorial introduction frames the thematic issue along three themes of networked processes: identity and identification; interaction patterns in online communities; and challenges and cautionary notes concerning social media organizing. A diverse range of country contexts, as well as theoretical and methodological approaches illustrated in this issue, represent the multifaceted research that scholars can undertake to understand networked organizing on social media.
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Daly, Alan J., Yi-Hwa Liou, Miguel Del Fresno, Martin Rehm, and Peter Bjorklund. "Educational Leadership in the Twitterverse: Social Media, Social Networks, and the New Social Continuum." Teachers College Record: The Voice of Scholarship in Education 121, no. 14 (November 2019): 1–20. http://dx.doi.org/10.1177/016146811912101404.
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Leadership is one of the most examined concepts in the literature, and while the study of social networks is also gaining interest, the intersection between leadership and online social networks has received limited attention. The key notion underlying most leadership research is that the behaviors or attributes of a leader matter for a variety of outcomes. While offering valuable insights, this dominant view of leadership behavior and attributes underestimates the impact of social networks. Scholars are increasingly recognizing the importance of social processes involved in leading. Leadership has often been conceptualized as a process of influence toward an outcome. Social relationships through networks may provide leaders with the necessary infrastructure to access resources in achieving outcomes. Leadership from a network perspective emphasizes the interdependence reflected by a network of ties, which may ultimately moderate, influence, or determine the activity and movement of practices and knowledge.