Characteristics Of Online Social Networks Research Articles

Enhanced by mobility? Effect of users’ mobility on information diffusion in coupled online social networks

Online social networks have gradually become crucial tools for users to exchange information. Two characteristics of online social networks should be underlined: first, individuals can freely leave or stay; second, information diffusion is more common on coupled online social platforms. However, very few research combines the above two aspects when studying the information diffusion in online social networks. Therefore, we establish an in-out-unacquired2-acquired 2-rejected2 (IO-S2P2R2) information diffusion model which investigates the time evolution of three types of users considering users’ mobility in coupled online social networks using mean-field theory. We analyze the theoretical threshold of information diffusion via linear analysis and find that the information diffusion threshold is related to the maximum eigenvalue of the super adjacency matrix. Moreover, by comparing the mean-field method with the Monte Carlo method, the consistency of the simulation results is obtained, which verifies the scientificity of our model. The results demonstrate the consistency of linear analysis and simulation experiments. Besides, based on the existing data sets, information diffusion rates and users’ mobility rates are positively correlated with the range of information diffusion, while information decline rates are negatively correlated with the range of information diffusion through the sensitivity analysis of parameters.

The Online Social Network and User Innovation

The wide use of social media technology boosts many online innovation platforms, providing effective communication channels for innovation spreading among online users. From the social network perspective, this paper investigates the impact of online interactive relations on user innovation by holistically examining online relations from relational and structural embeddedness, qualified by both the ego-centered and the entire network, respectively. User interaction data from LEGO Ideas are used to empirically test the effects of relational and structural characteristics of online social networks on users’ idea contributions. The results for relational characteristics reveal that the number of online ties has an inverted U-shaped relationship with user innovation, the strength of online ties positively affects user innovation, and neighbor characteristics cannot affect user innovation. For structural characteristics, both centrality and bridge location positively affect user innovation. The findings provide reasonable suggestions for both online users and innovation platforms.

The Online Social Network and User Innovation in the Context of an Online Innovation Platform

The wide use of social media technology boosts many online innovation platforms, providing effective communication channels for innovation spreading among online users. From the social network perspective, this paper investigates the impact of online interactive relations on user innovation by holistically examining online relations from relational and structural embeddedness, qualified by both the ego-centered and the entire network, respectively. User interaction data from LEGO Ideas are used to empirically test the effects of relational and structural characteristics of online social networks on users’ idea contributions. The results for relational characteristics reveal that the number of online ties has an inverted U-shaped relationship with user innovation, the strength of online ties positively affects user innovation, and neighbor characteristics cannot affect user innovation. For structural characteristics, both centrality and bridge location positively affect user innovation. The findings provide reasonable suggestions for both online users and innovation platforms.

Online misinformation about climate change

AbstractPolicymakers, scholars, and practitioners have all called attention to the issue of misinformation in the climate change debate. But what is climate change misinformation, who is involved, how does it spread, why does it matter, and what can be done about it? Climate change misinformation is closely linked to climate change skepticism, denial, and contrarianism. A network of actors are involved in financing, producing, and amplifying misinformation. Once in the public domain, characteristics of online social networks, such as homophily, polarization, and echo chambers—characteristics also found in climate change debate—provide fertile ground for misinformation to spread. Underlying belief systems and social norms, as well as psychological heuristics such as confirmation bias, are further factors which contribute to the spread of misinformation. A variety of ways to understand and address misinformation, from a diversity of disciplines, are discussed. These include educational, technological, regulatory, and psychological‐based approaches. No single approach addresses all concerns about misinformation, and all have limitations, necessitating an interdisciplinary approach to tackle this multifaceted issue. Key research gaps include understanding the diffusion of climate change misinformation on social media, and examining whether misinformation extends to climate alarmism, as well as climate denial. This article explores the concepts of misinformation and disinformation and defines disinformation to be a subset of misinformation. A diversity of disciplinary and interdisciplinary literature is reviewed to fully interrogate the concept of misinformation—and within this, disinformation—particularly as it pertains to climate change.This article is categorized under:Perceptions, Behavior, and Communication of Climate Change > Communication

Linking Network Characteristics of Online Social Networks to Individual Health: A Systematic Review of Literature

ABSTRACT Social networks have long been viewed as a structural determinant of health. With the proliferation of digital technologies, numerous studies have examined the health implications of online social networks (OSNs). However, the mechanisms through which OSNs may influence individual health are poorly understood. Employing a social network approach, this paper presents a systematic review of the literature examining how network characteristics of OSNs are linked to individuals' health behavior and/or status. Drawing on keyword searches in nine databases, we identified and analyzed 22 relevant articles from 1,705 articles published prior to 2017. The findings show that individual health is associated with a number of network characteristics, including both individual-level attributes (e.g., centrality) and network-level attributes (e.g., density, clustering). All of the included studies (n = 22) have focused on egocentric networks, and nine studies also collected whole network data of online health communities. Based on our review, we highlight three fruitful areas in the application of OSNs in public health: (1) disease and risk detection, (2) disease prevention and intervention, and (3) health behavior change. However, the precise mechanisms and causal pathways through which OSNs affect health remain unclear. More theoretically grounded, longitudinal, and mixed methods research is needed to advance this line of research.

Social reputation loss model and application to lost-linking borrowers in a internet financial platform

A social reputation loss model for loss of social reputation upon borrower disconnection on internet financial platforms is proposed. Firstly, the characteristics of on-line social networks of the borrowers are analysed from P2P platform, Chat platforms, QQ platform, one-click help platform, etc. Secondly, the characteristics of offline social networks of the borrowers are analysed in terms of blood, geographical, business, academic, heart, and ethnic relationships. Thirdly, from the six main factors, such as amount of default funds, disconnection time point, status of joint guarantee performance, project success probability, the amount and severity of network punishment, the impacts on the social reputation of lost-link borrowers are evaluated. Then, by quantifying these six main influencing factors, we establish a social reputation loss model on the lost-linking borrowers in P2P platform, and explore the relationship between borrower disconnection time and social reputation loss. The work proves that the social reputation loss of borrowers gradually decreases with the delay of disconnection time and other mathematical propositions. Finally, the applications of the model are discussed. The impacts of dynamic changes of the project success probability, disconnection time and amount of network punishment on the social reputation loss of borrowers are analysed. Through this study, an innovative calculating method for the loss of social reputation of borrowers who are out of touch on internet financial platforms is given.

Depressive Symptoms Predict Characteristics of Online Social Networks

PurposeThere is a substantial body of literature that examines depression or well-being as outcomes of social media use, but there are fewer studies that seek to understand how mental health may lead to different patterns of online interactions. The purpose of the present study was to examine how depressive symptoms may predict subsequent structural characteristics of the online social network. MethodsData came from Time 3 and Time 5 of a longitudinal study on the effects of maltreatment on adolescent development. At Time 3, adolescents reported on their depressive symptoms (n = 319), and at Time 5, a subsample was enrolled in the Facebook data collection (n = 133). An application downloaded the friend list, and network metrics were computed. Path models examined the main effect of depressive symptoms at Time 3 on Facebook social network measures. ResultsThe coefficients indicated that higher levels of depressive symptoms at Time 3 predicted fewer Facebook friends (smaller size), fewer ties between friends (lower average degree), more components, and fewer friends in the main component of the network. ConclusionsDepression may alter how youth form and maintain online friendships. Using social network characteristics may help identify youth at risk for serious mental illness.

The Impact of Emotion on the Information Diffusion Model in Online Social Network

In order to characterize the information propagation accurately on online social network, we propose an optimized SEIR information diffusion model. Firstly, the model considers the emotional factor of every node, which is a dynamic parameter in propagation process. The model defines five possible states: susceptible, exposed, removed, positive and negative infected. Every node attached to a specific emotion value, the dynamic interaction among these emotion values is produced in the diffusion process. We analyse the new mechanism of information dissemination and establish the mean-field equations. As we all know, the information dissemination is affected by user’s emotion, user’s degree and other factors. By simulating information diffusion process on real social Weibo, we analyse the density of users and the effect of some factors in the diffusion process. Simulation results agree well with the theoretical analysis, and it shows that the optimized model fits the characteristics of online social networks.

The Spreading of Information in Online Social Networks through Cellular Automata

Epidemic dynamics in complex networks have been extensively studied. Due to the similarity between information and disease spreading, most studies on information dynamics use epidemic models and merely consider the characteristics of online social networks and individual’s cognitive. In this paper, we propose an online social networks information spreading (OSIS) model combining epidemic models and individual’s cognitive psychology. Then we design a cellular automata (CA) method to provide a computational method for OSIS. Finally, we use OSIS and CA to simulate the spreading and evolution of information in online social networks. The experimental results indicate that OSIS is effective. Firstly, individual’s cognition affects online information spreading. When infection rate is low, it prevents the spreading, whereas when infection rate is sufficiently high, it promotes transmission. Secondly, the explosion of online social network scale and the convenience of we-media greatly increase the ability of information dissemination. Lastly, the demise of information is affected by both time and heat decay rather than probability. We believe that these findings are in the right direction for perceiving information spreading in online social networks and useful for public management policymakers seeking to design efficient programs.

Social network analysis: Characteristics of online social networks after a disaster

Social media, such as Twitter and Facebook, plays a critical role in disaster management by propagating emergency information to a disaster-affected community. It ranks as the fourth most popular source for accessing emergency information. Many studies have explored social media data to understand the networks and extract critical information to develop a pre- and post-disaster mitigation plan.The 2016 flood in Louisiana damaged more than 60,000 homes and was the worst U.S. disaster after Hurricane Sandy in 2012. Parishes in Louisiana actively used their social media to share information with the disaster-affected community − e.g., flood inundation map, locations of emergency shelters, medical services, and debris removal operation. This study applies social network analysis to convert emergency social network data into knowledge. We explore patterns created by the aggregated interactions of online users on Facebook during disaster responses. It provides insights to understand the critical role of social media use for emergency information propagation. The study results show social networks consist of three entities: individuals, emergency agencies, and organizations. The core of a social network consists of numerous individuals. They are actively engaged to share information, communicate with the city of Baton Rouge, and update information. Emergency agencies and organizations are on the periphery of the social network, connecting a community with other communities. The results of this study will help emergency agencies develop their social media operation strategies for a disaster mitigation plan.

Effect of Perceived Relational Characteristics of Online Social Network on e-WOM and Purchase Intention: Exploring Mediating Role of Trust

This paper explores the effect of perceived online social network characteristics and interpersonal trust on formation of attitude and intention to pass along electronic word of mouth about online stores as well as intention to purchase from those stores which use online social media marketing. Tie strength, homophily, embeddedness, cohesiveness and social capital have been considered as antecedents of trust, which lead to formation of attitude and intention to pass along electronic word of mouth as well as to purchase. The proposed conceptual model, based on existing literature, is empirically verified with 424 online social media users, employing partial least square. This study is among the very few empirical investigations done on antecedents of trust in online social media marketing focusing only on perceived relational characteristics of online social networks.

Effect of perceived relational characteristics of online social network on e-WOM and purchase intention: exploring mediating role of trust

This paper explores the effect of perceived online social network characteristics and interpersonal trust on formation of attitude and intention to pass along electronic word of mouth about online stores as well as intention to purchase from those stores which use online social media marketing. Tie strength, homophily, embeddedness, cohesiveness and social capital have been considered as antecedents of trust, which lead to formation of attitude and intention to pass along electronic word of mouth as well as to purchase. The proposed conceptual model, based on existing literature, is empirically verified with 424 online social media users, employing partial least square. This study is among the very few empirical investigations done on antecedents of trust in online social media marketing focusing only on perceived relational characteristics of online social networks.

Proactive Cache Placement on Cooperative Client Caches for Online Social Networks

This paper investigates cache placement on a cooperative cache built from individual client caches in an online social network or web service. We use a service that maintains a mapping between content and the clients that cache it, and propose cache placement schemes that leverage relationships between clients (for example, social links) and workload statistics, proactively placing content on clients that are likely to access it. We evaluate efficacy through simulation, comparing our schemes against commonly used cache placement algorithms as well as optimal placement. We synthesize a workload to match characteristics of online social networks. Simulation results of our proposed caching schemes impose moderate network overhead and show considerable improvement to the client's cache hit ratio, even under churn.

Novel authentication procedures for preventing unauthorized access in social networks

Online Social Network (OSN) is the most widely used platform to communicate with one another. It is fast and cheap when compared to other modes of communication. However, Online Social Network profiles are being hacked often by employing various types of malicious attacks. Most of the times the attackers are successful in accessing the OSN account which illustrates that the present authentication mechanisms are not efficient enough. Once an online social network account is being hacked, it can be misused widely and the hacker makes the authorized user unable to login to the account by changing the login credentials. Security in OSN must be provided and it must prevent the attacks aimed by the attackers. However, to prevent unauthorized access in OSN a novel authentication procedure is needed and the novel authentication mechanism must abide the social network platform’s characteristics. This paper considers the attackers who aim to access the OSN account in an unauthorized manner and presents two novel authentication mechanisms to prevent the OSN platform. The proposed procedures make use of users’ chatting module statistics and relationship circle statistics to authenticate the users in Online Social Networks. This can be done by Multi kernel Fuzzy C-Means (MKFCM) Algorithm and Group Search Optimizer (GSO). These novel authentication procedures abide the OSN characteristics, as it makes use of Chatting and Relationship module.

A Novel Rumor Propagation Model on Social Networks

In information age, the malevolent spreading of rumours on social networks put forward a new challenge to the security of network and society, it is extremely important to study the inherent laws of rumour spreading in online social networks and propose effective control strategies for rumours. In this paper, based on cellular automaton model, we propose a new rumour spreading model. We first show the propagation characteristics of online social networks rumours spread. Then experimental simulation is carried out under periodic boundary constraints in the process of rumour spread, and the result is compared with real data. In addition, the immunisation strategy to suppress the rumour spreading is analysed with detailed scenarios. The results show that the new model is indeed able to characterise the propagation behaviour on online social networks.

Why Do People Use Social Networks?

Online social networking (OSN) sites such as Facebook, YouTube, and Twitter are among the most popular sites around the World. In the case of Mexico, these sites are considered to be in the top. Users have different tools for reading and sharing information with his friends and/or contacts and for searching for new users that might have common interests. These sites have changed the way people get connected to each other on the web. The popularity of these sites is represented on its registered users: as today Facebook has about 500 million, and Twitter about 175 million. As these numbers grow, we believe that there is a great opportunity to study critical characteristics of online social network in order to identify the key success factors based on endusers’ perception. Identifying such factors would provide important information for improving current information systems by including social software characteristics as well as to design new high impact applications for online social networks. This paper presents the results obtained through a focus group study to identify the most important issues and perceptions about OSN. Results give us an idea where and what we should be doing for future research in the subject.

A framework for online social networking features

Article history: Received December 2, 2013 Accepted 8 May 2014 Available online May 15 2014 Social networks form a basis for maintaining social contacts, finding users with common interests, creating local content and sharing information. Recently networks have created a fundamental framework for analyzing and modeling the complex systems. Users' behavior studies and evaluates the system performance and leads to better planning and implementation of advertising policies on the web sites. Therefore, this study offers a framework for online social networks' characteristics. In terms of objective, this survey is practical descriptive. Sampling has been done among 384 of graduate students who have good experiences of membership in online social network. Confirmatory factor analysis is used to evaluate the validity of variables in research model. Characteristics of online social networks are defined based on six components and framework's indexes are analyzed through factor analysis. The reliability is calculated separately for each dimension and since they are all above 0.7, the reliability of the study can be confirmed. According to our research results, in terms of size, the number of people who apply for membership in various online social networking is an important index. In terms of individual preference to connect with, people who are relative play essential role in social network development. In terms of homogeneity variable, the number of people who visit their friends’ pages is important for measuring frequency variable. In terms of frequency, the use of entertainment and recreation services is more important index. In terms of proximity, being in the same city is a more important index and index of creating a sense of belonging and confidence is more important for measuring reciprocity variable. © 2014 Growing Science Ltd. All rights reserved.

Exploring the Use of Egocentric Online Social Network Data to Characterize Individual Air Travel Behavior

The rapid growth of online social networking over the past decade has generated substantial amounts of data about individuals and their social relationships. Recent research studies investigating social relationships and travel behavior have sought connections between individuals’ social networks and socially related travel; however, to the authors’ knowledge, no study has pursued the use of online social networking data to do so. This study explores the use of online social network data in characterizing individuals’ air travel behavior. Data were collected through a web-based survey including information about individuals’ air travel history and online social network information, specifically participants’ Facebook networks. The data were then analyzed to address a series of hypotheses about the association between online social network characteristics (specifically Facebook) and air travel behavior, in particular, travel distance, leisure-related travel, and trip generation. This study found a positive relationship between the size and distribution of individuals’ Facebook social networks and both their engagement in air travel and the odds that their air travel will be leisure related or will include a leisure component.

Social capital development of college students through online social networks

Purpose: To understand how online social networks promote social capital development of college students. Design/methodology/approach: Qualitative and ethnographic, studied during an academic semester (5 months) the case of a group of 21 university students of Information Technology Management from a private school in Mexico. Was used participant observation, through Facebook, and the interview as data collection tools. Findings and Originality/value: Online social networks have the potential to encourage social capital development, because they promote, in different proportions, the relational dimensions of social capital: confidence, identification, sharing standards and the acquisition of expectations and obligations. The three main features that have online social networks to promote the development of social capital are: the possibility of sharing information resources, the ability to communicate both publicly and privately and the possibility of increasing the contacts network. Research limitations/implications: A) the activities carried out privately was not observed. B) Although there are many online social networks, only was analyzed the behavior of participants through Facebook. C) The profile of the participants of the community under study is quite homogeneous. Therefore, when interpreting the results, the level of generalization is reduced to communities with similar characteristics. Originality/value: Previous research has shown that online social networks can promote social capital development in college students. However, this paper identifies the specific characteristics of online social networks, and behaviors of college students, that allow such development.

Online social networks: A survey of a global phenomenon

Online social networks became a global phenomenon with enormous social as well as economic impact within a few years. Alone, the most popular online social network, Facebook, counts currently more than 850 million users worldwide. Consequently, online social networks attract a great deal of attention among practitioners as well as researchers. The goal of this article is to provide an overview of online social networks in order to contribute to a better understanding of this worldwide phenomenon. In this context, we address for example the following questions: What are the major functionalities and characteristics of online social networks? What are the users’ motives for using them and how did online social networks emerge and develop over time? What is the impact and value of online social networks from a business perspective and what are corresponding challenges and risks?