The special topic calls for papers on Modeling the Cross-Cultural Adaptation Process of Immigrants and such papers will appear in Cross-Cultural Communication as a special column.
Affiliated research area: Cross-Cultural, Cultural Differences, Communication
A quantitative method for social data analysis, which is based on the use of categorical data clustering, is introduced. More specifically, Some researchers employ categorical data clustering to analyze the cross-cultural adaptation process of immigrants in a foreign cultural environment. To assess the extent to which individuals adapt themselves in a strange cultural environment, an experiment was conducted, where a set of cross-cultural categorical data was generated by using a questionnaire over a number of immigrants who live in Greece. The key idea is to cluster the available categorical data and to treat these clusters as patterns, each of which corresponds to a certain level of adaptation capability. Then, they detect and analyze changes of these patterns through time. These changes directly indicate how the cross cultural adaptation process proceeds. In order to cluster the available data set they use the well-known ROCK algorithm.
In addition to the Review and Original Articles by invited speakers, we are inviting you to submit a relevant research paper on Modeling the Cross-Cultural Adaptation Process of Immigrants for consideration. Papers will be subject to normal peer review and must comply with the Guide for Authors.
To submit papers to the “Modeling the Cross-Cultural Adaptation Process of Immigrants” Special Topic, please go to http://www.cscanada.net. With your submission, please state clearly to the editor that your manuscripts are submitted to the Special Topic Modeling the Cross-Cultural Adaptation Process of Immigrants.
44th Hawaii International Conference on System Sciences - 2011
Related Journals (Special issue):
CSCanada Cross-Cultural Communication journal
Modeling the Cross-Cultural Adaptation Process of Immigrants Using Categorical Data Clustering ISBN: 0-7695-2504-0