scholarly journals Decentralized Online Social Network Using Peer-to-Peer Technology

2016 ◽  
Vol 5 (1-2) ◽  
Author(s):  
Manh Ha Tran ◽  
Van Sinh Nguyen ◽  
Synh Viet Uyen Ha
Keyword(s):  
Social Network ◽  
User Authentication ◽  
Online Social Network ◽  
Peer To Peer ◽  
Computing Services ◽  
Processing Power ◽  
The Social ◽  
User Data ◽  
And Performance ◽  
Super Peer

This paper presents a social network with a peer-to-peer architecture that facilitates social computing services in distributed environments. This social network aims to provide users the capability of managing the dissemination of user data, searching user data on the data silos of the network, and consolidating user data from various social networks. The social network employs a super peer peer-to-peer architecture that contains peers and super peers. Users use peers to participate the network and services. Peers with sufficient storage, bandwidth and processing power become super peers that support peers for complex operations such as user authentication or group communication. We have extended the Gnutella protocol to provide the authentication and posting services on the social network. The design of these services copes with the distributed setting of the social network. The evaluation of the prototyping social network has performed on a number of laboratory workstations to investigate its scalability, reliability and performance.

scholarly journals Detecting the Influencer on Social Networks Using Passion Point and Measures of Information Propagation †

2020 ◽  
Vol 12 (7) ◽  
pp. 3064 ◽  
Author(s):  
Tai Huynh ◽  
Hien Nguyen ◽  
Ivan Zelinka ◽  
Dac Dinh ◽  
Xuan Hau Pham
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Marketing Strategy ◽  
Online Social Network ◽  
Modern Method ◽  
Information Propagation ◽  
The Social ◽  
User Data ◽  
The Impact ◽  
Positive Results

Influencer marketing is a modern method that uses influential users to approach goal customers easily and quickly. An online social network is a useful platform to detect the most effective influencer for a brand. Thus, we have an issue: how can we extract user data to determine an influencer? In this paper, a model for representing a social network based on users, tags, and the relationships among them, called the SNet model, is presented. A graph-based approach for computing the impact of users and the speed of information propagation, and measuring the favorite brand of a user and sharing the similar brand characteristics, called a passion point, is proposed. Therefore, we consider two main influential measures, including the extent of the influence on other people by the relationships between users and the concern to user’s tags, and the tag propagation through social pulse on the social network. Based on these, the problem of determining the influencer of a specific brand on a social network is solved. The results of this method are used to run the influencer marketing strategy in practice and have obtained positive results.

scholarly journals Social Network Analysis Visualization

2015 ◽  
pp. 257-270
Author(s):  
Mohana Shanmugam ◽  
Yusmadi Yah Jusoh ◽  
Rozi Nor Haizan Nor ◽  
Marzanah A. Jabar
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Social Network ◽  
Future Research ◽  
Research Gaps ◽  
The Social ◽  
Network Studies ◽  
Academic Study

The social network surge has become a mainstream subject of academic study in a myriad of disciplines. This chapter posits the social network literature by highlighting the terminologies of social networks and details the types of tools and methodologies used in prior studies. The list is supplemented by identifying the research gaps for future research of interest to both academics and practitioners. Additionally, the case of Facebook is used to study the elements of a social network analysis. This chapter also highlights past validated models with regards to social networks which are deemed significant for online social network studies. Furthermore, this chapter seeks to enlighten our knowledge on social network analysis and tap into the social network capabilities.

scholarly journals Online social networks as formal learning environments: Learner experiences and activities

2012 ◽  
Vol 13 (1) ◽  
pp. 144 ◽  
Author(s):  
George Veletsianos ◽  
Cesar Navarrete
Keyword(s):  
Social Network ◽  
Social Networking ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
Learning Experience ◽  
Online Social Network ◽  
Online Course ◽  
Formal Learning ◽  
The Social

<p>While the potential of social networking sites to contribute to educational endeavors is highlighted by researchers and practitioners alike, empirical evidence on the use of such sites for formal online learning is scant. To fill this gap in the literature, we present a case study of learners’ perspectives and experiences in an online course taught using the Elgg online social network. Findings from this study indicate that learners enjoyed and appreciated both the social learning experience afforded by the online social network and supported one another in their learning, enhancing their own and other students’ experiences. Conversely, results also indicate that students limited their participation to course-related and graded activities, exhibiting little use of social networking and sharing. Additionally, learners needed support in managing the expanded amount of information available to them and devised strategies and “workarounds” to manage their time and participation.<br /><strong></strong></p>

Collaborative Finance and Its Hurdles to Overcome

2020 ◽  
pp. 239-262
Author(s):  
Elisabet Ruiz-Dotras ◽  
Krystyna Mitręga-Niestrój
Keyword(s):  
Social Network ◽  
Social Interaction ◽  
Financial Literacy ◽  
Financial Services ◽  
Peer To Peer ◽  
Online Networks ◽  
The Social ◽  
Finance Development ◽  
Personal Trust ◽  
Financial Issues

Using survey data from an online Spanish university, real and perceived financial literacy levels, social interactions and personal trust with the social network are measured as key elements for collaborative finance development. This is the first study regarding the factors that may affect the use of collaborative finance. Results show levels of financial literacy are quiet low as in prior studies and individuals consider that the bank manager, friends, and parents can manage financial issues better than them, with the last two peers being those who most trust to discuss financial issues. The findings also provide information about how little individuals trust online networks when it comes to financial matters. Besides, respondents interact moderately with their social network missing the benefits of peer-to-peer learning. Overall, lack of financial literacy, low social interaction, and personal trust may be affecting the short use of collaborative financial services.

Building Online Social Networks to Engage Female Students in Information Systems

2015 ◽  
Vol 10 (4) ◽  
pp. 33-51
Author(s):  
Jaymeen R. Shah ◽  
Hsun-Ming Lee
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Information Systems ◽  
Online Social Networks ◽  
Social Networking Sites ◽  
Role Models ◽  
Online Social Network ◽  
Research Process ◽  
Female Students ◽  
The Social

During the next decade, enrollment growth in Information Systems (IS) related majors is unlikely to meet the predicted demand for qualified IS graduates. Gender imbalance in the IS related program makes the situation worse as enrollment and retention of women in the IS major has been proportionately low compared to male. In recent years, majority of high school and college students have integrated social networking sites in their daily life and habitually use these sites. Providing female students access to role models via an online social network may enhance their motivation to continue as an IS major and pursue a career in IS field. For this study, the authors follow the action research process – exploration of information systems development. In particular, a Facebook application was developed to build the social network connecting role models and students. Using the application, a basic framework is tested based on the gender of participants. The results suggest that it is necessary to have adequate number of role models accessible to students as female role-models tend to select fewer students to develop relationships with a preference for female students. Female students likely prefer composite role models from a variety of sources. This pilot study yields valuable lessons to provide informal learning fostered by role modeling via online social networks. The Facebook application may be further expanded to enhance female students' interests in IS related careers.

The Evolution of Coworker Networks

2008 ◽  
pp. 280-293 ◽  
Author(s):  
Arianna Dal Forno
Keyword(s):  
Social Network ◽  
Work Team ◽  
Combinatorial Explosion ◽  
Team Members ◽  
Team Selection ◽  
The Social ◽  
Two Factors ◽  
Human Experiments ◽  
And Performance ◽  
Selection Agent

When selecting work team members several behavioral components concur. In this chapter we are interested in investigating the effects of these components in terms of team selection, agent aggregation and performance of groups. A computational model, together with a theoretical approach and the results of two human experiments where subjects interact in a similar game, allow us to identify some of the most important determinants. Our results suggest that the occurrence of two factors is crucial: the presence of leaders as aggregators of knowledge and agents being able to expand and improve their higher profit projects. It is particularly evident the threefold role the leaders have. First, they increase the social network of other agents making possible projects otherwise impossible. Second, they state the pace of a balanced growth in terms of social network, while taming the otherwise combinatorial explosion. Finally, they help selecting one of the theoretically possible equilibria.

scholarly journals Understanding attribute and social circle correlation in social networks

2019 ◽  
pp. 1228-1242
Author(s):  
PRANAV NERURKAR ◽  
MADHAV CHANDANE ◽  
SUNIL BHIRUD
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Network ◽  
Real Life ◽  
Coarse Grained ◽  
Unified Framework ◽  
Community Discovery ◽  
Social Circle ◽  
The Social ◽  
Circle Formation

Social circles, groups, lists, etc. are functionalities that allow users of online social network (OSN) platforms to manually organize their social media contacts. However, this facility provided by OSNs has not received appreciation from users due to the tedious nature of the task of organizing the ones that are only contacted periodically. In view of the numerous benefits of this functionality, it may be advantageous to investigate measures that lead to enhancements in its efficacy by allowing for automatic creation of customized groups of users (social circles, groups, lists, etc). The field of study for this purpose, i.e. creating coarse-grained descriptions from data, consists of two families of techniques, community discovery and clustering. These approaches are infeasible for the purpose of automation of social circle creation as they fail on social networks. A reason for this failure could be lack of knowledge of the global structure of the social network or the sparsity that exists in data from social networking websites. As individuals do in real life, OSN clients dependably attempt to broaden their groups of contacts in order to fulfill different social demands. This means that ‘homophily’ would exist among OSN users and prove useful in the task of social circle detection. Based on this intuition, the current inquiry is focused on understanding ‘homophily’ and its role in the process of social circle formation. Extensive experiments are performed on egocentric networks (ego is user, alters are friends) extracted from prominent OSNs like Facebook, Twitter, and Google+. The results of these experiments are used to propose a unified framework: feature extraction for social circles discovery (FESC). FESC detects social circles by jointly modeling ego-net topology and attributes of alters. The performance of FESC is compared with standard benchmark frameworks using metrics like edit distance, modularity, and running time to highlight its efficacy.

A Novel Method to Dynamically Fix Threshold for Node Neighbourhood Based Link Prediction Techniques

2020 ◽  
Vol 15 (1) ◽  
pp. 17-34
Author(s):  
Anand Kumar Gupta ◽  
Neetu Sardana
Keyword(s):  
Social Network ◽  
Link Prediction ◽  
Binary Classification ◽  
Online Social Network ◽  
Threshold Value ◽  
Classification Problem ◽  
Similarity Score ◽  
The Social ◽  
Comparative Results ◽  
Prediction Techniques

The objective of an online social network is to amplify the stream of information among the users. This goal can be accomplished by maximizing interconnectivity among users using link prediction techniques. Existing link prediction techniques uses varied heuristics such as similarity score to predict possible connections. Link prediction can be considered a binary classification problem where probable class outcomes are presence and absence of connections. One of the challenges in classification is to decide threshold value. Since the social network is exceptionally dynamic in nature and each user possess different features, it is difficult to choose a static, common threshold which decides whether two non-connected users will form interconnectivity. This article proposes a novel technique, FIXT, that dynamically decides the threshold value for predicting the possibility of new link formation. The article evaluates the performance of FIXT with six baseline techniques. The comparative results depict that FIXT achieves accuracy up to 93% and outperforms baseline techniques.

The role of individual-social-technology fit in online social network value development: an empirical study

Info ◽  
2015 ◽  
Vol 17 (5) ◽  
pp. 66-81 ◽  
Author(s):  
ChienHsing Wu ◽  
Shu-Chen Kao ◽  
Hsin-Yi Liao
Keyword(s):  
Social Network ◽  
Online Social Network ◽  
Social Software ◽  
Social Technology ◽  
Content Type ◽  
The Social ◽  
Social Features ◽  
Individual Features ◽  
The Individual

Purpose – The purpose of this study is to reveal the role of individual–social–technology fit in online social network (OSN) value development. The social software features (e.g. communication and interaction), social features (e.g. privacy and trust) and individual features (e.g. sense of belonging and self-disclosure) are considered fitting forms to describe the OSN value. Implications and suggestions are addressed. Design/methodology/approach – The literature review on social software, the social and individual characteristics and the research gap with respect to OSN value is presented. The research arguments are then hypothesized, and research model used to describe the proposed role is examined empirically. The research targeted mobile phone users as the subjects, and the extent of the activities of these users on OSN for both work and studies. A salient investigation explores the moderation effect of gender. The research results are obtained, and the findings are revealed on the basis of 468 social software users. Findings – The significant effect of individual–social–technology fit on OSN value development is presented through the satisfaction of both participation and sharing information, and knowledge about this fit is verified. The interplay of social software, social and individual features contributes significantly to individual–social–technology fit development, implying that OSN value development is not a single issue. OSN value development should be considered concurrently with technological, personal and social issues. Research limitations/implications – The empirical study confirms that fitness analysis produces a systematic outcome, in which all elements (e.g. social, technology and individual) are required to cooperate with one another to maximize the OSN value. An individual adopts online channels to communicate with others; thus, the benefits may be a multidimensional issue instead of only a single information service issue. They also consider building an equal social relationship to be important, as it enables diverse propositions, maintains acceptable privacy and behaves on faith to enhance the fit of technology features and individual features to value development. The subjects also likely accepted the fact that emotion generation is important for the advantage of fit of technology features and social features, thereby likely benefitting OSN value development. Originality/value – The OSN does not only add new values to the society but also brings new effects on social development, especially in terms of social cognition from virtual community formation, development and creation. Although existing studies in the literature present the important aspects and antecedents linked significantly to OSN value development, these studies also insufficiently discuss the effect of fit of these facets on OSN value development. This exploratory study mainly aims to propose and examine the individual–social–technology fit model through an empirical investigation. The main argument of the study is that when a positive and healthy virtual society is developed through social software, the individual and social characteristics, as well as the social software features, should be defined with a suitable fit to promote the social networking value.

scholarly journals Adaptive Data Placement for Improving Performance of Online Social Network Services in a Multicloud Environment

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Seunghee Han ◽  
Bosung Kim ◽  
Jaemin Han ◽  
Kyehee Kim ◽  
JooSeok Song
Keyword(s):  
Social Network ◽  
Online Social Network ◽  
Data Placement ◽  
Network Services ◽  
Resource Contention ◽  
Redundant Data ◽  
User Data ◽  
Placement Algorithm ◽  
Using Data ◽  
Resource Status

The existing online social network (OSN) services in a multiple-cloud (Multicloud) environment use replications to store user data for improving the service performance. However, it not only generates tremendous traffic for synchronization between data but also stores considerable redundant data, thus causing large storage costs. In addition, it does not provide dynamic load balancing considering the resource status of each cloud. As a result, it cannot cope with the degradation of performance caused by the resource contention. We introduce an adaptive data placement algorithm without the replications for improving the performance of the OSN services in the Multicloud environment. Our approach is designed to avoid server overhead using data balancing technique, which locates data from a cloud to another according to the amount of traffic. To provide acceptable latency delay, it also considers the relationship between users and the distance between user and cloud when transferring data. To validate our approach, we experimented with actual users’ locations and times of use collected from OSN services. Our findings indicate that this approach can reduce the resource contention by an average of more than 59%, reduce storage volume to at least 50%, and maintain the latency delay under 50 ms.

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