scholarly journals Subjective Well-Being, Poverty and Ethnicity in South Africa: Insights from an Exploratory Analysis

2006 ◽  
Vol 80 (2) ◽  
pp. 313-341 ◽  
Author(s):  
Daniel F. Neff



2018 ◽  
Vol 28 (4) ◽  
pp. 284-290
Author(s):  
David Morton ◽  
Dalena van Rooyen ◽  
Danie Venter ◽  
Lena Andersson




2016 ◽  
Vol 19 (2) ◽  
pp. 232-248 ◽  
Author(s):  
Talita Greyling

The influx of asylum-seekers and refugees from across Africa into democratic South Africa has increased significantly. The aim of this paper is to determine the factors that influences the expect well-being of this unique group. Expected well-being is an important determinant of both the decision to migrate and the choice of a country of destination. Knowledge about this determinant therefore informs refugee policies. The results show that only a few of the factors found in the literature explaining the expected well-being of voluntary migrants also explain the expected well-being of forced migrants. However, a number of factors found in the literature that explain the subjective well-being and well-being in general of refugees and asylum-seekers also went towards explaining the expected well-being of this group. These factors include: government assistance, culture, the time spent in South Africa, economic factors, crime, refugee status, reasons for leaving the home countries and the number of people staying in a house in the receiving country. The findings of this study emphasise the differences between forced and voluntary migrants and highlight the factors that influence the expected well-being of forced migrants. These in turn shed light on migration decisions and the choice of destination countries.



Author(s):  
H. Andrew Schwartz ◽  
Lyle H. Ungar

Researchers have long measured people’s thoughts, feelings, and personalities using carefully designed survey questions, which are often given to a relatively small number of volunteers. The proliferation of social media, such as Twitter and Facebook, offers alternative measurement approaches: automatic content coding at unprecedented scales and the statistical power to do open-vocabulary exploratory analysis. We describe a range of automatic and partially automatic content analysis techniques and illustrate how their use on social media generates insights into subjective well-being, health, gender differences, and personality.



2020 ◽  
Vol 15 (3) ◽  
pp. 403-421
Author(s):  
Xiaoxi Dong ◽  
Lilia C. Dibello ◽  
Mehmet Türegün ◽  
Ruth A. Ban




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