Applying the Islamic marketing ethics among small scale business Muslimpreneurs during Covid19 MCO: A comparison among types of social network system (SNS)

2021 ◽  
Author(s):  
M. S. Muhammad Taufik ◽  
P. R. Mohd Faizal ◽  
A. R. Abdul Qayyum ◽  
M. A. Noorfazreen ◽  
Nor Afifa
Keyword(s):  
Social Network ◽  
Marketing Ethics ◽  
Small Scale ◽  
Network System

scholarly journals Formation of raiding parties for intergroup violence is mediated by social network structure

2016 ◽  
Vol 113 (43) ◽  
pp. 12114-12119 ◽  
Author(s):  
Luke Glowacki ◽  
Alexander Isakov ◽  
Richard W. Wrangham ◽  
Rose McDermott ◽  
James H. Fowler ◽  
...  
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Social Dynamics ◽  
Small Scale ◽  
East African ◽  
Nomadic Pastoralists ◽  
Social Network Structure ◽  
The Social ◽  
Total Impact ◽  
Social Network Position

Intergroup violence is common among humans worldwide. To assess how within-group social dynamics contribute to risky, between-group conflict, we conducted a 3-y longitudinal study of the formation of raiding parties among the Nyangatom, a group of East African nomadic pastoralists currently engaged in small-scale warfare. We also mapped the social network structure of potential male raiders. Here, we show that the initiation of raids depends on the presence of specific leaders who tend to participate in many raids, to have more friends, and to occupy more central positions in the network. However, despite the different structural position of raid leaders, raid participants are recruited from the whole population, not just from the direct friends of leaders. An individual’s decision to participate in a raid is strongly associated with the individual’s social network position in relation to other participants. Moreover, nonleaders have a larger total impact on raid participation than leaders, despite leaders’ greater connectivity. Thus, we find that leaders matter more for raid initiation than participant mobilization. Social networks may play a role in supporting risky collective action, amplify the emergence of raiding parties, and hence facilitate intergroup violence in small-scale societies.

scholarly journals A Social Network-Based Examination on Bid Riggers’ Relationships in the Construction Industry: A Case Study of China

Buildings ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 363
Author(s):  
Liang Xiao ◽  
Kunhui Ye ◽  
Junhong Zhou ◽  
Xiaoting Ye ◽  
Ramadhani Said Tekka
Keyword(s):  
Social Network ◽  
Construction Industry ◽  
Small Scale ◽  
High Concentration ◽  
Market Shares ◽  
The Social ◽  
Network Method ◽  
Solid Foundation

Collusive bidding has been an insidious issue in the construction industry. Bidders initiate collusive networks of various sizes to win market shares. The popularity of collusive bidding networks affects market fairness and erodes the interests of market players. Although considerable research efforts were made to diagnose collusive bidding networks, there remains a gap in knowledge regarding the relationships bid riggers use to engage in the networks. Therefore, this study used the social network method, where two hundred sixteen collusion cases were collected from China to test these relationships. The results show that collusive bidding networks were characterized by sparseness, a small scale, a high concentration, and strong randomness. Three types of collusive bidding networks were also detected: contractual, spontaneous, and shadow. Furthermore, these collusive bidding networks had discrepancies regarding participants’ identities, forms of collusive bids, and the determination of bid winners. It was found that the proposed social network model of deliberating bid riggers’ relationships lays a solid foundation for the detection of collusive bidding in the construction sector.

scholarly journals An Investigation of the Social Network System Competencies of High School Students in Japan

2018 ◽  
Vol 13 (05) ◽  
pp. 4 ◽  
Author(s):  
Masami Yoshida
Keyword(s):  
High School ◽  
High School Students ◽  
Social Network ◽  
Performance Criteria ◽  
Network System ◽  
School Students ◽  
Mean Values ◽  
The Social ◽  
Significant Difference ◽  
The Difference

We investigated the Social Network System (SNS) competencies of high school students in Japan. Student groups (from cities or regional areas) and the opinions of their teachers were compared. Twenty-five UNESCO criteria in three competency categories were selected. By two-way analysis of variance and paired-comparisons, we detected a significant difference in the opinions of students and teachers. Although the magnitude of the difference was small, by Dunnett’s multiple comparisons, the city and regional groups also differed from each other. Performance criteria items of risk awareness were valued the highest and most important in all groups; whereas technical skills and socio-cultural skills were reported as less proficient and less important by all groups. Classification of SNS-type was used, and the data of SNS sites with which the students were familiar and the mean values of related performance criteria items were applied to view the situation of students. By this approach, we confirmed that students are savvy in navigating socializing SNSs. Based on our findings, we propose important learning and societal-public activities relevant to SNSs.

Large-scale dynamic social data representation for structure feature learning

2020 ◽  
Vol 39 (4) ◽  
pp. 5253-5262
Author(s):  
Xiaoxian Zhang ◽  
Jianpei Zhang ◽  
Jing Yang
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Large Scale ◽  
Dynamic Change ◽  
Feature Learning ◽  
Data Representation ◽  
Feature Representation ◽  
Small Scale ◽  
Dynamic Feature ◽  
Dynamic Social Networks

The problems caused by network dimension disasters and computational complexity have become an important issue to be solved in the field of social network research. The existing methods for network feature learning are mostly based on static and small-scale assumptions, and there is no modified learning for the unique attributes of social networks. Therefore, existing learning methods cannot adapt to the dynamic and large-scale of current social networks. Even super large scale and other features. This paper mainly studies the feature representation learning of large-scale dynamic social network structure. In this paper, the positive and negative damping sampling of network nodes in different classes is carried out, and the dynamic feature learning method for newly added nodes is constructed, which makes the model feasible for the extraction of structural features of large-scale social networks in the process of dynamic change. The obtained node feature representation has better dynamic robustness. By selecting the real datasets of three large-scale dynamic social networks and the experiments of dynamic link prediction in social networks, it is found that DNPS has achieved a large performance improvement over the benchmark model in terms of prediction accuracy and time efficiency. When the α value is around 0.7, the model effect is optimal.

scholarly journals Social Network Supported Process Recommender System

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Yanming Ye ◽  
Jianwei Yin ◽  
Yueshen Xu
Keyword(s):  
Social Network ◽  
Structure Analysis ◽  
Business Process ◽  
Recommender System ◽  
Process Modeling ◽  
Network System ◽  
The Social ◽  
Social Features ◽  
Matching Degree ◽  
Process Structure

Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

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