**Social Trust: Evaluating Node Influential Capability in Social Networks**

Renewable Energy and Distributed Resources in Smart Grids" by Ignacio Aravena, Anthony Papavasiliou and Alex Papalexopoulos analyzes the distributed system for the management of the short-term operations of power systems. They propose optimization algorithms for both the levels of the distribution grid and high voltage grids. Numerical results are also

This book also contains a chapter covering the programming aspect of parallel and distributed computing. For the study of parallel programming, the general processing units (GPUs) are considered. GPUs have received attention for parallel computing because their manycore capability offers a significant speedup over traditional general purpose processors. In the chapter entitled "GPU Computing Taxonomy" by Abdelrahman Ahmed Mohamed Osman, a new classification mechanism is proposed to facilitate the employment of GPU for solving the single program multiple data problems. Based on the number of hosts and the number of devices, the GPU computing can be separated into four classes. Examples are included to

The final two chapters focus on the software aspects of the distributed and parallel computing. Software tools for the wikinomics-oriented development of scientific applications are presented in the chapter entitled "Distributed Software Development Tools for Distributed Scientific Applications" by Vaidas Giedrimas, Anatoly Petrenko and Leonidas Sakalauskas. The applications are based on service-oriented architectures. Flexibilities are provided so that codes and components deployed can be reused and transformed into a service. Some proto-

The chapter entitled "DANP-Evaluation of AHP-DSS" by Wolfgang Ossadnik, Benjamin Föcke and Ralf H. Kaspar evaluates the Analytic Hierarchy Process (AHP)-supporting software for the use of adequate Decision Support Systems (DSS) for the management science. The corresponding software selection, evaluation criteria, evaluation framework, assessments and evaluation results are provided in detail. Issues concerning the evaluation assisted by

These chapters offer comprehensive coverage of parallel and distributed computing from engineering and science perspectives. They may be helpful to further stimulate and promote the research and development in this rapid growing area. It is also hoped that newcomers or researchers from other areas of disciplines desiring to learn more about the parallel and

Department of Computer Science and Information Engineering, National Taiwan Normal

illustrate the features of each class. Efficient coding techniques are also provided.

types are given to demonstrate the effectiveness of the proposed tools.

parallel and distributed computing are also addressed.

distributed computing will find this book useful.

Address all correspondence to: whwang@csie.ntnu.edu.tw

**Author details**

Wen-Jyi Hwang

University, Taipei, Taiwan

included for illustrating the effectiveness of the algorithms.

2 Recent Progress in Parallel and Distributed Computing

Yap Hock Yeow and Lim Tong‐Ming

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/67021

#### Abstract

Social networking sites are platforms that facilitate large-scale information sharing activities in recent years. Many organizations analyze social networking traffic to gain market insights in order to observe the latest market trends. These analyses also allow organizations to identify key promoters who have strong influences on these social networking platforms to promote their products or services. It is hypothesized that social trust plays an important role in influential propagation, and it is able to increase the rate of success in influencing other social nodes in a social network. This research performs large-scale experimental simulation to study the influential outcome with and without the presence of social trust in the social nodes.

Keywords: influence diffusion, influential maximization, social trust, trusted influence, domain specified trust influence

### 1. Introduction

In the last decade, the number of social networking site users have increased leap and bound [1]. Social networking sites are great places for one to express opinions toward people, products or services. Social networking sites disseminate information by influencing current and new nodes within the social networking environment. Gesenhues [2], Paquette [3] and Quesenberry [4] found that recommendations on the social networking sites often highly regarded by consumers. A research carried out by Ewing [5] showed that consumers often rely extensively on social networking sites referrals to make consumer decisions. In a world with many uncertainties, interacting with anonymous often raises trust issue. Trust presented various concerns especially for business operators where information spreading on the social networking sites may alter reputational impacts toward a business. There are many trustrelated studies [6–9] that were conducted by different researchers, and most of them strongly

© 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

supported that trust played a key role in affecting one's decision. Without doubt, the use of social networking sites for large-scale information sharing and message spreading is effective [10–12], but there are still some shortcomings that need to be addressed where it includes online user-generated contents and the assessment on their credibility. This research suggests two approaches to investigate trust as a factor on influential maximization and trust with domain specified social nodes as a factor on influential maximization. The objective of this research is to uncover trust value of each social node by evaluating social node opinion consistency and then to evaluate the rate of successful influenced social nodes with and without the presence of trust and domain specified trust. This research formulates two hypothesizes. They are as follows: (1) trust is able to positively increase the rate of successfully influenced social nodes within a social networking site, and (2) trust is able to positively increase the rate of successfully influenced social nodes from trusted social networking site users that are in the same domain. This research also reviewed extensively on trust and trust-related implementation issues on social networking sites. This article will report the results gathered from the findings and presents a discussion of the two hypothesizes with a conclusion.
