HOW SOCIAL MEDIA COMMUNICATION EFFECTS ON MASS VS. LUXURY FASHION BRANDS’ SUSTAINABLE MARKETING: A CROSS CULTURAL STUDY BETWEEN KOREA AND GERMANY

2018 ◽  
Vol 2018 ◽  
pp. 1588-1589
Author(s):  
Hyun Min Kong ◽  
◽  
Alexander Witmaier ◽  
Eunju Ko
2017 ◽  
Vol 9 (1) ◽  
pp. 82
Author(s):  
Salvador Madrigal Moreno ◽  
Jaime Gil Lafuente ◽  
Gerardo Gabriel Alfaro Calderón ◽  
Flor Madrigal Moreno

Virtual social networks (VSN) represent a phenomenon that continues reconfiguring the social dynamics. They have gone from the embryonic stage to a stage of maturity where it is observed that the context uses and appropriates those considered useful, giving them the use that seems to fit. Thus, Mexico and Spain contexts have specific characteristics and conditions. The aim of this study is to describe the access and appropriations of VSN, both in Mexico and in Spain and to show the challenges they face. The structure of this research is primarily an introduction to explain social networks as a current media phenomenon to later compare how each context has accessed, used and fitted these social networks into their own contexts. Finally, it will be discussed how Spain and Mexico face their challenges and last how each country treat the social media either as a threat or as an opportunity.


2014 ◽  
Vol 31 (1) ◽  
pp. 59-73 ◽  
Author(s):  
Robert LaRose ◽  
Regina Connolly ◽  
Hyegyu Lee ◽  
Kang Li ◽  
Kayla D. Hales

2019 ◽  
Vol 11 (2) ◽  
pp. 12-34
Author(s):  
Yuan Xue ◽  
Yilu Zhou

The study of national culture and cultural differences has immense value in today's business world. However, contemporary cross-cultural study instruments are subjective to many biases and intensive in terms of human labor. On the other hand, social media data offers tremendous opportunities for cross-cultural studies. However, it cannot be used directly as input for existing cross-cultural study applications in social science for being unstructured and noisy. In this work, the authors develop a text mining application called Social Media Associative Group Analysis (SMAGA). It effectively discovers information relevant to cultural values from social media data and represent such information using AGA verbal associations tuples. Experimental results show that the SMAGA framework can generate meaningful results in support of cross-cultural studies with much higher efficiency than traditional cross-cultural study instruments. This research underlines the emerging trend of developing text mining applications to automate cross-cultural and other types of social science studies.


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