A Study on the Difference between Social Network Analysis and Text Network Analysis

2021 ◽  
Author(s):  
Duk Jin Kim ◽  
Woo Yeong Lee ◽  
Do Hyung Kim
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
The Difference ◽  
Text Network Analysis

Do shareholder's independency and board size affect synergies from cross-border bank mergers and acquisitions? International evidence from social network analysis

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sheng-Hung Chen ◽  
Feng-Jui Hsu ◽  
Ying-Chen Lai
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Ordinary Least Squares ◽  
Standard Errors ◽  
Board Size ◽  
Content Type ◽  
Cross Border ◽  
The Difference

PurposeThere is little known globally on the association among the independent shareholder, board size and merger and acquisition (M&A) performance. This paper addresses the global issue about cross-border M&A in banking sector, particularly exploring the role of difference in the independent shareholder and board size between acquirer and target banks on synergy gains based on the international study.Design/methodology/approachBased on cross-border bank M&As data on 59 deals from 1995 to 2009, we initially apply social network analysis techniques to explore the country connectedness of the acquirer-target banks in cross-border M&As. Ordinary least squares (OLS) with robust standard errors is further used to investigate synergy gains within the difference in the degree of bank independent shareholder and board sizes between the acquirer and target banks.FindingsOur results indicate that the acquiring banks are generally interconnected with the targeted banks and that some of acquiring banks are clearly concentrated in Asian countries including China, Hong Kong, and Philippines. Moreover, we find that cross-border M&As with larger difference in independent shareholders between the bidder and target bank would result in higher synergy gains in all cases of takeover premiums on 1 day, 1 week and 4 weeks. In addition, financial differences between the bidder and target banks have a significant impact on synergetic gains, a topic not explored in previous studies. There is no evidence that institutional and governance differences between bidder and target bank have significant cross-border impacts on takeover premiums with respect to 1 day, 1 week and 4 weeks, respectively.Originality/valueThis paper contributes to the literature by exploring the international issue about the role of difference in the degree of bank independent shareholder and board sizes between acquirer and target banks on synergy gains. Based on bank cross-border M&As data on 59 deals from 1995 to 2009, we initially apply social network analysis to explore the country connectedness of acquirer-target bank in cross-border M&As, while ten ordinary least squares (OLS) with robust standard errors is used to investigate synergy gains within the difference in the degree of bank independent shareholder and board sizes between acquirer and target banks.

The Relationship between Governance Networks and Social Networks: Progress, Problems and Prospects

2017 ◽  
Vol 16 (4) ◽  
pp. 331-341 ◽  
Author(s):  
Gaby Ramia ◽  
Roger Patulny ◽  
Greg Marston ◽  
Kyla Cassells
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Dark Side ◽  
The Social ◽  
Power Differentials ◽  
Governance Networks ◽  
The Difference ◽  
The Relationship

A governance networks literature that uses social network analysis has emerged, but research tends to be more technical than conceptual. This restricts its accessibility and usefulness for non-quantitative scholars and practitioners alike. Furthermore, the literature has not adequately appreciated the importance of informal networking for the effective operation of governance networks. This can hinder inter-disciplinary analysis. Through a critical review, this article identifies four areas of challenge for the governance networks literature and offers four corresponding, complementary sets of concepts from the social network analysis field: (a) the difference between policy networks and governance networks, (b) the role and status of people in governance networks, (c) the ‘dark side’ of networks and the role of power differentials within them and (d) network evaluation and the question of ‘what works’ in network management. The article argues that a less technical, more accessible account of social network analysis offers an additional lens through which to view governance networks.

scholarly journals A Method of Vehicle Route Prediction Based on Social Network Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Ning Ye ◽  
Zhong-qin Wang ◽  
Reza Malekian ◽  
Ying-ya Zhang ◽  
Ru-chuan Wang
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Model Parameters ◽  
Data Set ◽  
Vehicle Route ◽  
Route Prediction ◽  
The Matrix ◽  
The Difference ◽  
Leave One Out

A method of vehicle route prediction based on social network analysis is proposed in this paper. The difference from proposed work is that, according to our collected vehicles’ past trips, we build a relationship model between different road segments rather than find the driving regularity of vehicles to predict upcoming routes. In this paper, firstly we depend on graph theory to build an initial road network model and modify related model parameters based on the collected data set. Then we transform the model into a matrix. Secondly, two concepts from social network analysis are introduced to describe the meaning of the matrix and we process it by current software of social network analysis. Thirdly, we design the algorithm of vehicle route prediction based on the above processing results. Finally, we use the leave-one-out approach to verify the efficiency of our algorithm.

Social network analyses of positive and negative relationships among Japanese preschool classmates

2009 ◽  
Vol 33 (3) ◽  
pp. 193-201 ◽  
Author(s):  
Keiko K. Fujisawa ◽  
Nobuyuki Kutsukake ◽  
Toshikazu Hasegawa
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Positive Relationships ◽  
Network Analyses ◽  
The Difference ◽  
Negative Relationships ◽  
Social Network Analyses

Using social network analysis, we investigated the characteristics of social networks composed of positive relationships (positive network: PN) and negative relationships (negative network: NN) in classrooms of Japanese 3- and 4-year-olds. Analysis of “density” showed that PNs were denser than NNs among 4-year-olds but that this was not the case among 3-year-olds. The difference between the probability of dyads of girls forming cliques, between PNs and NNs, was larger than that for dyads of boys or mixed-sex dyads. Four-year-olds formed cliques more often in PNs than in NNs, compared to 3-year-olds. This study showed that both sex combination of dyads and age affect the quantified properties of social networks among preschoolers.

How Should We Study Relational Structure? Critically Comparing the Epistemological Positions of Social Network Analysis and Field Theory

Sociology ◽  
2019 ◽  
Vol 53 (4) ◽  
pp. 762-778
Author(s):  
Sourabh Singh
Keyword(s):  
Field Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Ties ◽  
Relational Structure ◽  
History Of ◽  
Epistemological Position ◽  
The Difference ◽  
Epistemological Break

I argue that the main difference between two schools of relational sociology – field theory and social network analysis – lies in the difference between their respective epistemological stances rather than between their ontological assumptions. While social network analysts have developed sophisticated quantitative, qualitative and mixed methods, they epistemologically rely on their commonsensical understanding of relational structure. In contrast, field theorists are expected to study relational structure by making an epistemological break from their commonsensical understanding of relational structure. Social network analysts’ epistemological position reveals only social ties as the form of relational structure. Field theory’s epistemological position reveals multiple forms of relational structure, including but not limited to those formed by social ties. The main lesson to be learned is that relational sociologists must develop their notion of relational structure by investigating the history of contests among field actors over the meaning of being a member of their field.

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