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.

Sentiment analysis of foreign tourists to Bangkok using data mining through online social network

2017 ◽  
Author(s):  
Taweesak Kuhamanee ◽  
Nattaphon Talmongkol ◽  
Krit Chaisuriyakul ◽  
Wimol San-Um ◽  
Noppadon Pongpisuttinun ◽  
...  
Keyword(s):  
Data Mining ◽  
Social Network ◽  
Sentiment Analysis ◽  
Online Social Network ◽  
Using Data

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.

Applying Personalized Recommendation for Social Network Marketing

E-Marketing ◽  
2012 ◽  
pp. 137-150 ◽  
Author(s):  
Leila Esmaeili ◽  
Ramin Nasiri ◽  
Behrouz Minaei-Bidgoli
Keyword(s):  
Social Network ◽  
Business Models ◽  
Online Social Network ◽  
Age Groups ◽  
User Preferences ◽  
Ease Of Use ◽  
Personalized Recommendation ◽  
Network Marketing ◽  
New Business ◽  
Using Data

The competition among manufacturers and service providing companies as well as the widespread presence of electronic processes has introduced new business models that need special e-Marketing. Social network marketing is one of the most recent types of marketing. Today, due to their flexibility and ease of use, social networks have fallen in the center of attention for users of various age groups. The variety of online social network groups, some of which are created with commercial goals, has made users uncertain and skeptical; on the other hand, in today’s competitive market, companies are seeking their potential and actual customers. To solve this problem, this paper introduced a group recommender system which, using data mining techniques and information theory, offers customized recommendations based on user preferences. Supposing that users in each group share similar characteristics, heterogeneous members are identified and removed. Unlike other methods, in special cases where the user does not have relationships with other members or when an activity history for the user does not exist, this method could yet offer recommendations.

Finding the Trustworthiness Nodes from Signed Social Networks

2013 ◽  
Vol 22 (4) ◽  
pp. 471-485
Author(s):  
Hui Li ◽  
Shu Zhang ◽  
Xia Wang
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Network ◽  
Network Services ◽  
Edge Weight ◽  
The Public ◽  
Signed Social Networks ◽  
Public Dataset ◽  
Negative Relationships ◽  
The Prestige

AbstractOnline social network services have brought a kind of new lifestyle to the world that is parallel to people’s daily offline activities. Social network analysis provides a useful perspective on a range of social computing applications. Social interaction on the Web includes both positive and negative relationships, which is certainly important to social networks. The authors of this article found that the accuracy of the signs of links in the underlying social networks can be predicted. The trust that other users impart on a node is an important attribute of networks. In this article, the authors present a model to compute the prestige of nodes in a trust-based network. The model is based on the idea that trustworthy nodes weigh more. To fulfill this task, the authors first attempt to infer the attitude of one user toward another by predicting signed edges in networks. Then, the authors propose an algorithm to compute the prestige and trustworthiness where the edge weight denotes the trust score. To prove the algorithm’s effectiveness, the authors conducted experiments on the public dataset. Theoretical analysis and experimental results show that this method is efficient and effective.

scholarly journals Adopción y Difusión de Innovación Social en las Redes Sociales Virtuales

2019 ◽  
pp. 197
Author(s):  
Joaquín Castillo de Mesa
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Online Social Network ◽  
Network Services ◽  
Redes Sociales ◽  
Frequent Use ◽  
Social Network Services ◽  
Para Determinar ◽  
Professional Information

La adopción masiva de las redes sociales virtuales por la sociedad y su uso frecuente han convertido a estos servicios en un universo paralelo de socialización. Esto ha permitido que se compartan cantidades masivas de información, también de carácter profesional, conformando el llamado Big Social Data.El objetivo de este artículo es analizar si los profesionales que desarrollan políticas sociales activas están usando las redes sociales virtuales para compartir información.Considerando como innovación el uso de las redes sociales virtuales para compartir información y conocimiento de carácter profesional, se indaga si los profesionales del trabajo social están adoptando esta innovación. A partir de un modelo experimental desarrollado en Málaga (España) se analiza, mediante etnografía virtual, la presencia, conectividad e interacción de los profesionales en las redes sociales virtuales. Por otra parte, mediante la metodología de análisis de redes sociales se profundiza en el análisis de la conectividad en la estructura social online observada para determinar quiénes son, en virtud de su posición, los líderes de opinión. Se indaga en cómo se adopta y difunde esta innovación prestando atención a la posible correlación entre la capacidad de liderazgo y el momento de adopción.Los resultados muestran que la difusión de la innovación analizada es muy rápida. Se detecta cierta correlación entre liderazgo y momento de adopción (Rogers, 1958), poniéndose en evidencia que los precursores en la adopción son aquellos que tienen menos poder en la estructura (Becker, 1970). Se discute sobre cómo afecta el poder en la adopción de innovación. Finalmente se reflexiona sobre el potencial de las redes sociales virtuales para el Trabajo Social.Society’s overwhelming adoption and frequent use of online social networks have transformed these services into the parallel universe of conventional socialization. They have allowed for the spread of massive amounts of information of all stripes, including professional information, and have thus brought to bear what we now know as Big Social Data.The aim of this paper is to analyze whether professionals involved in active social policies in the Province of Malaga (Spain) use social network services to share information and knowledge related to the field of social intervention.Starting from the premise that the applied use of social network services constitutes an innovation to share professional information and knowledge, we sought to analyze whether professional social workers are indeed adopting this innovation. Employing an experimental model developed in Malaga, their presence and activity on Facebook® have been observed and analyzed through the lens of virtual ethnography. Moreover, by way of social network analysis, we examined the connectedness within the structure of the observed online social network so as to determine, by virtue of one’s position, who the opinion leaders are. We also analyze how this innovation is spread and whether there is a possible correlation between leadership ability and moment of adoption.The obtained results demonstrate how social network services applied to social intervention are massively and frequently used by professionals, and the diffusion of this innovation is extremely swift. Moreover, a correlation between leadership and the time of adoption is evident. Nonetheless, the precursors still stand as those professionals who have less opportunities and less power within the structure (Becker, 1970). How power and influence affect the adoption of the innovation is discussed in detail. Finally, we ponder the great potential online social networks offer to the field of Social Work apropos to education on improving cooperation and the diffusion of information and knowledge amongst professionals as well as users.

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