How Much does Empathy Resemble Trust? Trust Radius and Interpersonal Empathy in South Korea

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Sumin Lee ◽  
◽  
Wonho Jang ◽  
Keyword(s):  
Empirical Relationship ◽  
Social Science Research ◽  
Science Research ◽  
Research Literature ◽  
Korean Society ◽  
Individual Level ◽  
The Social ◽  
Highly Correlated ◽  
The Individual ◽  
Demographic Background

This research attempts to 1) explore trust from a theoretical angle using various perspectives in the social science research literature and 2) reveal the empirical relationship between trust and empathy at the individual level. Although trust and empathy share similar characteristics when considered in the realm of theory, they have typically been probed in distinct disciplines. Hence, there is a need for interdisciplinary perspective that addresses two concepts together. Using the Social Attitude Survey for Korean Society data collected in 2021, this study conducted a correlation and multivariate analysis that examined how much trust and empathy resemble. The results show that trust radius and interpersonal empathy are highly correlated. Also, trust and empathy levels differ from individual to individual in terms of one’s socioeconomic and demographic background. From this comparison, we emphasize the importance of the macro level effect of trust and empathy.

Looking Beyond Demographics: Panel Attrition in the ANES and GSS

2014 ◽  
Vol 22 (3) ◽  
pp. 336-353 ◽  
Author(s):  
Laura Lazarus Frankel ◽  
D. Sunshine Hillygus
Keyword(s):  
Social Science Research ◽  
General Social Survey ◽  
Science Research ◽  
Drop Out ◽  
Panel Surveys ◽  
Individual Level ◽  
Demographic Predictors ◽  
Panel Attrition ◽  
The Individual ◽  
Data Collections

Longitudinal or panel surveys offer unique benefits for social science research, but they typically suffer from attrition, which reduces sample size and can result in biased inferences. Previous research tends to focus on the demographic predictors of attrition, conceptualizing attrition propensity as a stable, individual-level characteristic—some individuals (e.g., young, poor, residentially mobile) are more likely to drop out of a study than others. We argue that panel attrition reflects both the characteristics of the individual respondent as well as her survey experience, a factor shaped by the design and implementation features of the study. In this article, we examine and compare the predictors of panel attrition in the 2008–2009 American National Election Study, an online panel, and the 2006–2010 General Social Survey, a face-to-face panel. In both cases, survey experience variables are predictive of panel attrition above and beyond the standard demographic predictors, but the particular measures of relevance differ across the two surveys. The findings inform statistical corrections for panel attrition bias and provide study design insights for future panel data collections.

scholarly journals The Social Network within a Management Recruiting Firm: Network Structure and Output

2009 ◽  
Vol 8 (4) ◽  
Author(s):  
Neil Gandal ◽  
Charles King ◽  
Marshall Van Alstyne
Keyword(s):  
Network Structure ◽  
White Collar ◽  
Network Size ◽  
Information Flows ◽  
Individual Level ◽  
Unique Data ◽  
The Social ◽  
Highly Correlated ◽  
The Individual ◽  
The Relationship

To understand the relationship between information flows and white-collar output, we collected unique data on email communications to study the network connecting individuals in a management recruiting firm. We also gathered data on revenues and contracts at the individual level. Our empirical results suggest that the size of an individual's internal email network is more highly correlated with output than with the number of email messages, the time spent communicating, the external network size, and with all other measures of communication. This result suggests that a more favorable position in the network structure is associated with higher individual output.

A Tale of Two Cultures

2012 ◽  
Author(s):  
Gary Goertz ◽  
James Mahoney
Keyword(s):  
Social Sciences ◽  
Quantitative Research ◽  
Social Science Research ◽  
Measurement Data ◽  
Science Research ◽  
Quantitative Research Methods ◽  
Qualitative And Quantitative ◽  
The Social ◽  
Scientific Worldview ◽  
Different Cultures

Some in the social sciences argue that the same logic applies to both qualitative and quantitative research methods. This book demonstrates that these two paradigms constitute different cultures, each internally coherent yet marked by contrasting norms, practices, and toolkits. The book identifies and discusses major differences between these two traditions that touch nearly every aspect of social science research, including design, goals, causal effects and models, concepts and measurement, data analysis, and case selection. Although focused on the differences between qualitative and quantitative research, the book also seeks to promote toleration, exchange, and learning by enabling scholars to think beyond their own culture and see an alternative scientific worldview. The book is written in an easily accessible style and features a host of real-world examples to illustrate methodological points.

Designing and Evaluating Survey Instruments for Research in Human Issues in Horticulture

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 554c-554
Author(s):  
Sonja M. Skelly ◽  
Jennifer Campbell Bradley
Keyword(s):  
Survey Research ◽  
Survey Methodology ◽  
Human Subjects ◽  
Social Science Research ◽  
Reliability And Validity ◽  
Science Research ◽  
Survey Instrument ◽  
Measurement Tool ◽  
The Social ◽  
Survey Instruments

Survey research has a long precedence of use in the social sciences. With a growing interest in the area of social science research in horticulture, survey methodology needs to be explored. In order to conduct proper and accurate survey research, a valid and reliable instrument must be used. In many cases, however, an existing measurement tool that is designed for specific research variables is unavailable thus, an understanding of how to design and evaluate a survey instrument is necessary. Currently, there are no guidelines in horticulture research for developing survey instruments for use with human subjects. This presents a problem when attempting to compare and reference similar research. This workshop will explore the methodology involved in preparing a survey instrument; topics covered will include defining objectives for the survey, constructing questions, pilot testing the survey, and obtaining reliability and validity information. In addition to these topics some examples will be provided which will illustrate how to complete these steps. At the conclusion of this session a discussion will be initiated for others to share information and experiences dealing with creating survey instruments.

An Introduction to Statistical Models for Networks

2020 ◽  
pp. 218-233
Author(s):  
Valentina Kuskova ◽  
Stanley Wasserman
Keyword(s):  
Social System ◽  
Exponential Family ◽  
Behavioral Science ◽  
Social Science Research ◽  
Science Research ◽  
Uniform Distributions ◽  
The Social ◽  
Special Cases ◽  
Social And Behavioral Science ◽  
Network Methods

Network theoretical and analytic approaches have reached a new level of sophistication in this decade, accompanied by a rapid growth of interest in adopting these approaches in social science research generally. Of course, much social and behavioral science focuses on individuals, but there are often situations where the social environment—the social system—affects individual responses. In these circumstances, to treat individuals as isolated social atoms, a necessary assumption for the application of standard statistical analysis is simply incorrect. Network methods should be part of the theoretical and analytic arsenal available to sociologists. Our focus here will be on the exponential family of random graph distributions, p*, because of its inclusiveness. It includes conditional uniform distributions as special cases.

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