Current Status and Direction of User Perception Trends in Design through Non face to face Social Phenomenon: Focused on Social Network Big Data Keywords

2021 ◽  
Vol 15 (1) ◽  
pp. 101-111
Author(s):  
Minsub Shim
Keyword(s):  
Big Data ◽  
Social Network ◽  
Current Status ◽  
Social Phenomenon ◽  
User Perception ◽  
Face To Face ◽  
Network Big Data

A Novel Embedding Method for Information Diffusion Prediction in Social Network Big Data

2017 ◽  
Vol 13 (4) ◽  
pp. 2097-2105 ◽  
Author(s):  
Sheng Gao ◽  
Huacan Pang ◽  
Patrick Gallinari ◽  
Jun Guo ◽  
Nei Kato
Keyword(s):  
Big Data ◽  
Social Network ◽  
Information Diffusion ◽  
Embedding Method ◽  
Network Big Data ◽  
Diffusion Prediction

scholarly journals Social Network Big Data Hierarchical High-Quality Node Mining

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Dongning Jia ◽  
Bo Yin ◽  
Xianqing Huang
Keyword(s):  
Big Data ◽  
Social Network ◽  
Data Analysis ◽  
Shopping Mall ◽  
Network Data ◽  
Clustering Methods ◽  
Learning Mechanisms ◽  
Social Network Data ◽  
Analysis Methods ◽  
Network Big Data

Compared with the conventional network data analysis, the data analysis based on social network has a very clear object of analysis, various forms of analysis, and more methods and contents of analysis. If the conventional analysis methods are applied to social network data analysis, we will find that the analysis results do not reach our expected results. The results of the above studies are usually based on statistical methods and machine learning methods, but some systems use other methods, such as self-organizing self-learning mechanisms and concept retrieval. With regard to the current data analysis methods, data models, and social network data, this paper conducts a series of researches from data acquisition, data cleaning and processing, data model application and optimization of the model in the process of application, and how the formed data analysis results can be used for managers to make decisions. In this paper, the number of customer evaluations, the time of evaluation, the frequency of evaluation, and the score of evaluation are clustered and analyzed, and finally, the results obtained by the two clustering methods applied in the analysis process are compared to build a customer grading system. The analysis results can be used to maintain the current Amazon purchase customers in a hierarchical manner, and the most valuable customers need to be given key attention, combining social network big data with micro marketing to improve Amazon’s sales performance and influence, developing from the original single shopping mall model to a comprehensive e-commerce platform, and cultivating their own customer base.

scholarly journals Map the Gap: A Novel Approach Using Social Network “Big Data” to Determine the State of the Infectious Diseases Workforce With Regards to HIV

2015 ◽  
Vol 2 (suppl_1) ◽  
Author(s):  
Aditya Shah ◽  
Adam Treitman ◽  
Brian Wolf ◽  
Joumana Chaiban ◽  
Armand Krikorian
Keyword(s):  
Big Data ◽  
Social Network ◽  
Infectious Diseases ◽  
The State ◽  
Novel Approach ◽  
Network Big Data
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