|
Title:
|
ANALYSIS AND VISUALIZATION METHODS FOR TOPICAL BUSINESS NETWORKS |
|
Author(s):
|
Donghun Lee and Kwanho Kim |
|
ISBN:
|
978-989-8533-80-7 |
|
Editors:
|
Ajith P. Abraham, Jörg Roth and Guo Chao Peng |
|
Year:
|
2018 |
|
Edition:
|
Single |
|
Keywords:
|
Topical Extraction, Text Mining, Social Network Analysis, Visualization |
|
Type:
|
Poster/Demonstration |
|
First Page:
|
252 |
|
Last Page:
|
254 |
|
Language:
|
English |
|
Cover:
|
|
|
Full Contents:
|
click to dowload 
|
|
Paper Abstract:
|
The importance of convergence activities among business is increasing due to the necessity of designing and developing new products to satisfy various customers' needs. In particular business representatives with top decision-making are required to maintain network connections to obtain suitable convergence partners. It is important for business not only to make a large number of contacts, but also to understand the networking relationship with business with similar topic information. However, there is a difficult limit in collecting the topic information that can show the lack of current status of business and the technology and characteristics of business in industry sector. In this paper, we solve these problems through the topic extraction technique and analyze the business network in three aspects. Specifically, there are C,S,T-Layer models, and each model analyzes amount of business relationship, network centrality, and topic similarity. As a result of experiments using real data, it is necessary to activate network of strengthening network with highly centrally located companies when the corporate relationship is low. In addition, we confirmed through experiments that there is a need to activate the topic-based network if the topic similarity is low. |
|
|
|
|
|
|
