Specific Social Network Research Articles

The Influencing Factors of Intellectual Property Pledge Loan Trust: A Social Network Theory-Based Experimental Study

This paper studies the behavior of intellectual property pledge loan based on a specific social network and uses the method of experimental research to analyze the impact of factors on the comprehensive trust of intellectual property pledge loan. The results show that if direct cooperation records between enterprises and banks are complete, the larger the scale of cooperation, the higher the trust of intellectual property pledge loans, and the nearer the cooperation record to the present time, the greater the credibility of enterprise cooperation. If there is no direct cooperation record between enterprises and banks, or cooperation record is incomplete, in accordance with the trust evaluation of the recommended members on the intellectual property pledge loan enterprise, the smaller the degree of trust at a certain recommendation node, the lower the credibility of enterprises at this node correspondingly, and the lower the perceived risk tolerance of banks, the lower the cooperation satisfaction in the intellectual property pledge loan enterprises.

Identification of source social network of digital images using deep neural network

• A novel method is presented for the identification of image provenance. • It identifies if the image is taken with a camera or it has been downloaded from a specific social network. • It does not rely on hand-crafted fingerprints to learn the social network specific traces. • Transfer learning approach is used to learn the traces from the images transformed to the DCT or DWT domain. • The proposed method is robust in capturing the traces from the resized images. Identification of image provenance is one of the crucial tasks to be tackled in the field of image forensics . Due to the rapid growth in technology, a huge amount of digital images are shared among users through social networks which facilitates many malicious activities . Establishing the provenance of downloaded images is an important task that could help focus investigations in a specific direction. Such a task is based on the identification of unique fingerprints that are imprinted on images by the social network during the process of upload and download. Based on this, we propose a deep learning based approach that learns the unique traces from the images transformed to the discrete cosine and wavelet domains , to investigate whether the image under test originates directly from a camera or from a specific social network site . The proposed method is able to efficiently identify the specific social network of provenance of the downloaded images and outperforms the state-of-the-art techniques. The encouraging results on images represented in the wavelet domain obtained for the well-known datasets, namely, VISION, IPLAB, and FODB sheds the light into a new way of identifying the image provenance.

Towards a resilient perspective for the future of offshore platforms. Insights from a data driven approach

PurposeThis study aims to investigate the collective perception regarding the future of offshore platforms and frame the main categories of meanings associated by the community with the investigated phenomenon.Design/methodology/approachA data driven approach has been conducted. The collection of the peoples’ opinions has been realized on two specific social network communities as follows: Twitter and Instagram. The text mining processes carried out a sentiment and a cluster analysis.FindingsThe sentiment analysis of the most frequent words has been shown. The following four main homogeneous categories of words are emerged in relation to the decommissioning of offshore platforms: technological areas, green governance (GG), circular economy and socio-economic sphere.Research limitations/implicationsThe alternative use of the offshore platforms, including tourism initiatives, aquaculture, alternative energy generation, hydrogen storage and environmental research, could improve the resilience of communities by offering the development of new jobs and the growth of local and innovative green businesses.Practical implicationsThe adoption of a circular model and GG initiatives aims to limit the input of resources and energy, minimize waste and losses, adopt a sustainable approach and realize new social and territorial value.Originality/valueThe analysis underlines the importance to adopt a systems perspective, which takes into account the social, economic and environmental system as a whole, the different phenomena that occur and the variety of categories of stakeholders, from users to local governments that participate in the territorial development.

The role of social structure and dynamics in the maintenance of endemic disease.

Social interactions are required for the direct transmission of infectious diseases. Consequently, the social network structure of populations plays a key role in shaping infectious disease dynamics. A huge research effort has examined how specific social network structures make populations more (or less) vulnerable to damaging epidemics. However, it can be just as important to understand how social networks can contribute to endemic disease dynamics, in which pathogens are maintained at stable levels for prolonged periods of time. Hosts that can maintain endemic disease may serve as keystone hosts for multi-host pathogens within an ecological community, and also have greater potential to act as key wildlife reservoirs of agricultural and zoonotic diseases. Here, we examine combinations of social and demographic processes that can foster endemic disease in hosts. We synthesise theoretical and empirical work to demonstrate the importance of both social structure and social dynamics in maintaining endemic disease. We also highlight the importance of distinguishing between the local and global persistence of infection and reveal how different social processes drive variation in the scale at which infectious diseases appear endemic. Our synthesis provides a framework by which to understand how sociality contributes to the long-term maintenance of infectious disease in wildlife hosts and provides a set of tools to unpick the social and demographic mechanisms involved in any given host–pathogen system.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00265-021-03055-8.

Detection of Harassment Type of Cyberbullying: A Dictionary of Approach Words and Its Impact

The purpose of this paper is to analyse the effects of predatory approach words in the detection of cyberbullying and to propose a mechanism of generating a dictionary of such approach words. The research incorporates analysis of chat logs from convicted felons, to generate a dictionary of sexual approach words. By analysing data across multiple social networks, the study demonstrates the usefulness of such a dictionary of approach words in detection of online predatory behaviour through machine learning algorithms. It also shows the difference between the nature of contents across specific social network platforms. The proposed solution to detect cyberbullying and the domain of approach words are scalable to fit real-life social media, which can have a positive impact on the overall health of online social networks. Different types of cyberbullying have different characteristics. However, existing cyberbullying detection works are not targeted towards any of these specific types. This research is tailored to focus on sexual harassment type of cyberbullying and proposes a novel dictionary of approach words. Since cyberbullying is a growing threat to the mental health and intellectual development of adolescents in the society, models targeted towards the detection of specific type of online bullying or predation should be encouraged among social network researchers.

The Impact of Social Networks on the Development of Students’ Social Competence

The article analyzes the possibilities which virtual social networks provide for the development of youth’s social competence. The authors analyze the results of the survey on the students’ use of virtual social networks for communication. To achieve the purpose of the research and to determine the essence and significance of social competence we used methods of analysis, synthesis and generalization of research works; the method of observation was used to identify the peculiarities of communication between young people in social networks; the method of questionnaire was used to collect information about the students’ preferences regarding the choice of specific virtual social networks for communication. The results of observations and questionnaires confirmed the suggestion that the time young people spend on online communication and surfing the Internet is increasing. The survey results of 107 students studying in Year 1-4 at the pedagogical university (Ukraine) let us make a conclusion that they often stay on virtual social networks browsing them from 2 to 4 times a day (51,4%). Almost a third of students are constantly on social networks. The most popular ones appeared to be Instagram (83,1%) and Facebook (28%). With the help of social networks students actively communicate with group mates (80,4%), friends and family (78,5%). Further research is planned to consider the ways how to avoid the negative effects of the Internet on students’ personality.

Going Viral: The 3 Rs of Social Media Messaging during Public Health Emergencies.

Going Viral: The 3 Rs of Social Media Messaging during Public Health Emergencies.

Quantifying individual influence in leading-following behavior of Bechstein\u2019s bats

Leading-following behavior as a way of transferring information about the location of resources is wide-spread in many animal societies. It represents active information transfer that allows a given social species to reach collective decisions in the presence of limited information. Although leading-following behavior has received much scientific interest in the form of field studies, there is a need for systematic methods to quantify and study the individual contributions in this information transfer, which would eventually lead us to hypotheses about the individual mechanisms underlying this behaviour. In this paper we propose a general methodology that allows us to (a) infer individual leading-following behaviour from discrete observational data and (b) quantify individual influence based on methods from social network analysis. To demonstrate our methodology, we analyze longitudinal data of the roosting behavior of two different colonies of Bechstein’s bats in different years. Regarding (a) we show how the inference of leading-following events can be calibrated from data making it a general approach when only discrete observations are available. This allows us to address (b) by constructing social networks in which nodes represent individual bats and directed and weighted links—the leading-following events. We then show how social network theory can be used to define and quantify individual influence in a way that reflects the dynamics of the specific social network. We find that individuals can be consistently ranked regarding their influence in the information transfer. Moreover, we identify a small set of individuals that play a central role in leading other bats to roosts. In the case of Bechstein’s bats this finding can direct future studies on the individual-level mechanisms that result in such collective pattern. More generally, we posit that our data-driven methodology can be used to quantify leading-following behavior and individual impact in other animal systems, solely based on discrete observational data.

PINTEREST ЯК ЕФЕКТИВНИЙ ІНСТРУМЕНТ ПРОСУВАННЯ НЕПРИБУТКОВИХ ОРГАНІЗАЦІЙ В УМОВАХ ТЕНДЕНЦІЇ МАРКЕТИНГУ У СОЦІАЛЬНИХ МЕДІА

In the age of IT, social media acquired a status of fast, powerful and dynamic ways to share information. Social medias like Pinterest, Facebook, Twitter and many others, are used in everyday life by billions of people, especially youth. As a result, efficiency issues of informational potential are especially important in the context of informatization of society. In this article, I analyzed the necessity of marketing on social media for nonprofit organisations. Underlined the problem of brand promotion on social media caused by the high level of competition. During the research, I analyzed the effectiveness of underrated social media - Pinterest, that allows you to save a great amount of pictures with integrated social functions. Pinterest is not just a social media, that works differently than Facebook or Twitter, where likes are extremely valuable. The main purpose of Pinterest in contrast to other social media is SEO - account description, boards and every pin. I described benefits, gained by every non-profit organization, using SMM strategies. With a properly developed strategy, Pinterest search engine will be working excellent for B2B and B2C segments. I outlined potential methods of promoting nonprofit organizations via this social media and developed the activity strategy for this organizations. Since Pinterest users are mostly USA and Europe citizens - a solvent segment, ready for buying goods and services on social media, and the target audience of nonprofits needs these investments, it is proved that Pinterest will be a useful tool due to its inexpensiveness, providing stable traffic, easy and even free to promote posts. Pinterest marketing strategy is important for businesses of any size, in any industry. It is important to develop a strategy for a specific social network, because each has its own algorithm. Non-profit organizations should build a strategy on Pinterest, analyze and optimize it. The most important Pinterest feature for non-profit organizations is that Pinterest, unlike other social media, is future-oriented. It should be underlined that Pinterest is an ideal tool for young sites and startups with a limited budget.

The Mediating Effect of Bridging Social Capital Between Social Media Usage and Affective Attitude

In this work, the authors develop and test a theoretical model that investigates the mediating effect of bridging social capital between usage of a brand specific social network site and consumer attitude towards the brand. Specifically, they see how usage of online social network sites drives consumer purchase intent, using university football as a domain to test the model. They find that bridging social capital is indeed a mediating construct between the university's sports social networking site usage and affective attitude towards the team brand. As social network site usage increases, both injunctive norms (perceptions about the expectations of referent others) and descriptive norms (perceptions of the actual behavior of referent others) increase. They show that these influence emotional reward, in the form of increased bridging social capital, which in turn influences affective attitude towards the brand. The findings contribute to understanding how consumer tribes form on online forums and how subjective norms influence affective consumer attitude.

Career-related Networking Strategies of Korean Skilled Women in Japan

This paper discusses the shifting networks of newcomer Korean female migrants in Japan, focusing on their changing form and function as mechanism of their career mobility. It argues that limited or structuralized networks for migrant women no longer work for recent Korean female migrants since they tend to build their new networks or bring their networks from the home country in the process of migration. For the argument, the current research also examines the process of network building in the context of Korean women’s three stages of career development: recruitment, maintenance and expansion, and circulation. It underscores the importance of understanding the diversified and changed function of specific social networks. The findings show that the social networks of Korean women, who moved to Japan in the 1980s and 1990, are concentrated in the localized ethnic networks. On the other hand, these networks have shifted in a sense that Korean women who moved later in the 2000s have engaged in competitive professional networks regardless of ethnicity and gender. Furthermore, the most recent wave of Korean migrants conducts transnational cooperative networks that they access and expand across the globe, which support their career in the global labor market.

Efficient Strategy Mining for Football Social Network

With the growing popularity of social network in sport, it expresses the social relationships between individuals and facilitates realistic applications, e.g., social event mining and discovery. Sport network as a specific social network has been widely studied in research and commercial fields. However, most of the existing works utilize a simplex strategy to improve certain indicators in the team and do not consider the effect of strategy adjustment based on the current situation. In this paper, we study the problem of efficient strategy mining in football social network. To address this problem, we propose a quantitative way to combine the aspects of coordination, adaptability, flexibility, and tempo into a passing network, which notably improves the timeliness and information content of the existing network. On this basis, we design a suppression function to express the impact of strategy. Then, we propose a novel passing network and group cooperation scheme based on quantified team performance to obtain the efficient strategies. At last, the experimental results show that, based on the performance of the same team, our optimized passing network has a higher winning rate in practice.

Parameter estimation in a 3‐parameter p‐star random graph model

AbstractAn important issue in social network analysis refers to the development of algorithms for estimating parameters of a social network model, using data available from the network itself. This entails solving an optimization problem. In the paper, we propose a new method for parameter estimation in a specific social network model, namely, the so‐called p‐star random graph model with three parameters. The method is based on the mean‐field approximation of the moments associated with the three subgraphs defining the model, namely: the mean numbers of edges, 2‐stars, and triangles. A modified gradient ascent method is applied to maximize the log‐likelihood function of the p‐star model, in which the components of the gradient are computed using approximate values of the moments. Compared to other existing iterative methods for parameter estimation, which are computationally very expensive when the number of vertices becomes large, such as gradient ascent applied to maximum log‐likelihood and maximum log‐pseudo‐likelihood estimation, the proposed approach has the advantage of a much cheaper cost per iteration, which is practically independent of the number of vertices.

School engagement as a mediator in students’ social relationships and academic performance: a survey based on CiteSpace

Purpose In studies related to education, sociology and economics, the relationship between students’ social relationships and their academic performance is one of the most important research topics; a large number of research studies have focused on it. This study aims to analyze the previous studies about social interaction and academic performance and attempts to reveal the underlying mechanism. Design/methodology/approach This study uses CiteSpace to analyze 1,843 articles on social relationships and academic performance from 2001 to 2019. According to the co-cited literature network results in CiteSpace, this study proposes an adapted conceptual framework of the relationship between social relationships and academic performance. This paper further examines more studies about the two most-cited articles in the co-cited literature network for better understanding. Findings From the results of the co-cited literature network, this study determines that school engagement is an important mediator between social relationships and academic performance. This paper further examines studies on school engagement and determine that, along with the self-determination theory, school engagement is influenced by multiple components of self-determination theory: autonomy, competence and relatedness. Originality/value According to the visual result in CiteSpace, this study examines a research trend in which researchers scholars start to conduct micro and detailed empirical research on the impact of the specific social networks on academic performance because of the progress of information technology. Therefore, based on the previous literature that we have analyzed, this study predicts that the trend of using information technology, such as data mining or data analysis, in this academic field will become a mainstream practice in the future.

An efficient approach to identify social disseminators for timely information diffusion

In recent years, motivated by many practical applications such as viral marketing, researchers have paid significant attention to the circulation of information on social networks. The influential nodes that can influence the largest part of social networks are an essential topic in social network analysis. Most present solutions address the issue of discovering the influential nodes that could maximize influence effectiveness rather than minimize the cost of the information diffusion. In this paper, we investigate the circulation of emergency information, such as timely production promotion or disaster information, through a social network. These are real-life problems that have a significant effect in a very short time. We focus on how to minimize the total cost for all users in a specific social network to receive such information. We propose an efficient k-best social disseminator discovering algorithm in which the total diffusion cost on spreading timely information for each user in this social network is minimized.

Institutionalizing Social Network Solutions in Tertiary Educational Institutions

As in other socioeconomic spheres, social networks and media are veritable tools for education as they provide easy channels for information and knowledge exchange and their trendy nature make them very attractive and portable among the young and old. However, these applications are fraught with security challenges ranging from surveillance to invasion of privacy and unwarranted tampering with user data regardless of the seemingly impressive underlying rights of users as claimed by the vendors as to user accounts. Various vulnerabilities are reported daily as well as data leaks. There appears to be no end to these unwarranted infringement on rights of users. Sadly, majority of the popular social networking platforms irrespective of their modus operandi are guilty of this silent crime. Users of such applications are often carried away with flashy features without paying reasonable attention to the security and privacy of their data. In many cases users appear to have relinquished their privacy rights to these platforms owing to the fact that many users who suffer data breaches are either ignorant of such or may not have the wherewithal to challenge the vendors through legal actions. Interestingly a large chunk of users are unaware of their fundamental rights on such platforms. This paper underscores the relevance of social networks and social media in tertiary education vis-à-vis the popularly used social networks and advocates for the evolution and institutionalizing of specific tertiary education social network (TESN) that captures the unique demands of students and lecturers. The rapid application development paradigm is used to demonstrate a prototype of a TESN that ensures privacy and security of user data. It is concluded that this application presents a comparative performance while offering institutional data protection, privacy and security of user data.

Social Networks Use Patterns among University Youth: The Validity and Reliability of an Updated Measurement Instrument

This article addresses the design and validation of an updated questionnaire that makes it possible to understand the use patterns and attitudes of university youth on social networks. The authors utilized a panel of 20 judges who were social media experts and a sample of 640 university students. The exploratory factor analysis (EFA) explained 66.523% of the total variance. The confirmatory factor analysis (CFA), carried out to verify the dimensional structure of the instrument, reflected the appropriate parameters. The reliability study showed a Cronbach’s alpha of 0.864. These data corroborated the development of a robust and reliable questionnaire. The resulting instrument did not contain items alluding to specific social networks (Facebook, Twitter, Instagram, or LinkedIn), but rather students’ usage patterns of them. The exclusion of items that referred to particular social networks during the research demonstrated a convergence in behavior on social media regardless of the nuances of each platform. This fact suggested that the platform was of secondary importance in the context of a new paradigm in which the type of use (viewing, posting, participating, or interacting) took precedence over the name of the network itself.

Revisiting international relations legacy on hegemony

Purpose This study aims to investigate the decline of American hegemony as one of the most prominent crises of the modern world order, from a broader perspective that transcends narrow traditional interpretations. The paper assumes that the September 11 events in 2001 have launched the actual decline in American hegemony. Tracing the evolution of US global strategy over the past two decades, the study seeks to analyze the main causes and repercussions of the decline of US hegemony, which would provide a bird’s eye view of what the current global system is going through. Design/methodology/approach The study investigates the decline in American hegemony through a longitudinal within-case analysis which focuses on the causal path of decline in hegemony in the case of the USA, since the events of September 11, 2001, and tries to identify the causal mechanisms behind this decline. Following George and Bennet (2005), the study uses process tracing to examine its research question. Process-tracing method seeks to identify the intervening causal process – causal chain or causal mechanisms or the steps in a causal process – that leads to the outcome of a particular case in a specific historical context (Mahoney, 2000; Bennet and Elman, 2006). The study chose this method, as it offers more potential for identifying causal mechanisms and theory testing (George and Bennet, 2005); it opted for a specific procedure, among the variety of process-tracing procedures listed by George and Bennet, which is the detailed narrative presented as a chronicle, accompanied by explicit causal hypotheses. Using this process tracing procedure, the study assumes that American hegemony has witnessed dramatic changes in the aftermath of critical junctures, particularly the events of September 11, 2001, and the financial crises, 2008, which contributed significantly to this decline. Consequently, it traces the impact of these events on the state of American hegemony, in light of the review of contributions of different theories on hegemony in the field of international relations, both traditional and critical. Consequently, introducing the theoretical framework used in the study (the four-dimensional model of hegemony), which transcends criticisms of previous theories. Findings The crises of the modern world order and the decline of American hegemony – being the main manifestation of such crises – revealed the inability of the traditional and critical approaches reviewed in the study to interpret this decline and those crises. The reason behind that was the inability of these interpretations to reflect the various dimensions of American hegemony and its decline since the September 11 events. This highlights the importance of using the four-dimensional model, which combines different factors in the analysis and has proved to be an appropriate model for studying the case of American hegemony and its decline after the events of September 11, as it deals with the phenomenon of hegemony as a social relationship based on specific social networks. Originality/value Despite the currency and relevance of the decline of US hegemony for both the academic and political world, the topic needed to be analyzed systemically and addressed in a thorough scientific way. Through the application of theoretical concepts into the analysis of empirical data, this study contributes to a field where too often the discourse about decline of American hegemony is led without the required theoretical or conceptual considerations.

Active Social Network Sites Use and Loneliness: the Mediating Role of Social Support and Self-Esteem

A growing body of research has documented the association between general social network sites use and loneliness, though results have not clarified whether social media increases or decreases loneliness. The relationships between specific social network sites use patterns and loneliness, as well as the mechanisms underlying this association, should be further examined. To address this issue, the current study investigated the mediating roles of social support and self-esteem between active social network sites use and loneliness. A sample of 390 undergraduate students (Mage = 19.39, SD = 0.95) anonymously completed the Active Social Network Sites Use Questionnaire, the Rosenberg Self-esteem Scale, the Multidimensional Scale of Perceived Social Support Scale, and the Emotional and Social Loneliness Scale in their classrooms. Latent variables structural equation modeling analysis indicated that: (a) active social network sites use was negatively associated with loneliness; (b) social support and self-esteem could significantly mediate the relationship between active social network sites use and loneliness, which contained two mediating paths: the simple mediating effect of social support and the sequential mediating effects of social support and self-esteem. These results coincide with previous research and extend them by examining the effects of how individuals use social media. Our understanding of how social media use helps to reduce the feeling of loneliness, as well as the intervention programs that aim to reduce loneliness, may benefit from these findings.

A DIVISION OF LABOR: THE ROLE OF BIG DATA ANALYSIS IN THE REPERTOIRE OF INTERNET RESEARCH METHODS

In recent years, large-scale analysis of log data from digital devices - often termed ""big data analysis"" (Lazer, Kennedy, King, & Vespignani, 2014) - have taken hold in the field of internet research. Through Application Programming Interfaces (APIs) and commercial measurement, scholars have been able to analyze social media users (Freelon 2014) and web audiences (Taneja, 2016) on an uprecedented scale. And by developing digital research tools, scholars have been able to track individuals across websites (Menchen-Trevino, 2013) and mobile applications (Ørmen & Thorhauge 2015) in greater detail than ever before. Big data analysis holds unique potential for studying communication in depth and across many individuals (see e.g. Boase & Ling, 2013; Prior, 2013). At the same time, this approach introduces new methodological challenges in the transparency of data collection (Webster, 2014), sampling of participants and validity of conclusions (Rieder, Abdulla, Poell, Woltering, & Zack, 2015). Firstly, data aggregation is typically designed for commercial rather than academic purposes. The type of data included as well as how it is presented depend in large part on the business interests of measurement and advertisement companies (Webster, 2014). Secondly, when relying on this kind of secondary data it can be difficult to validate the output or techniques used to generate the data (Rieder, Abdulla, Poell, Woltering, & Zack, 2015). Thirdly, often the unit of analysis is media-centric, taking specific websites or social network pages as the empirical basis instead of individual users (Taneja, 2016). This makes it hard to untangle the behavior of real-world users from the aggregate trends. Lastly, variations in what users do might be so large that it is necessary to move from the aggregate to smaller groups of users to make meaningful inferences (Welles, 2014). Internet research is thus faced with a new research approach in big data analysis with potentials and perils that need to be discussed in combination with traditional approaches. This panel explores the role of big data analysis in relation to the wider repertoire of methods in internet research. The panel comprises four presentations that each sheds light on the complementarity of big data analysis with more traditional qualitative and quantitative methods. The first presentation opens the discussion with an overview of strategies for combining digital traces and commercial audience data with qualitative interviews and quantitative survey methods. The next presentation explores the potential of trace data to improve upon the experimental method. Researcher-collected data enables scholars to operate in a real-world setting, in contrast to a research lab, while obtaining informed consent from participants. The third presentation argues that large-scale audience data provide a unique perspective on internet use. By integrating census-level information about users with detailed traces of their behavior across websites, commercial audience data combines the strength of surveys and digital trace data respectively. Lastly, the fourth presentation shows how multi-institutional collaboration makes it possible do document social media activity (on Twitter) for a whole country (Australia) in a comprehensive manner. A feat not possible through other methods on a similar scale. Through these four presentations, the panel aims to situate big data analysis in the broader repertoire of internet research methods.