Identifying the business and social networks in the domain of production by merging the data from heterogeneous internet sources

Dominik Kozjek (Author), Rok Vrabič (Author), Gregor Eržen (Author), Peter Butala (Author)

Abstract

People, companies, and institutions form networks as part of their technical, economic, and social activities. As a consequence, these networks have an influence on how companies conduct business. Recently, the Internet, professional, and scientific social networks have contributed to the ease and simplicity of the network forming process and the public availability of the corresponding data. We investigate whether useful information about the relationships between individuals, companies, and institutions for the domain of production can be extracted from publicly available, structured and unstructured data that is merged from various Internet sources. We demonstrate that relevant information about the structures of these networks can be obtained by merging publicly available data using a combination of advanced computational methods including web crawling, machine learning, and creating mash-ups of publicly available services. The feasibility and the applicability of the approach are shown for a case in the automotive domain. A potential use case of the resulting data is demonstrated, showing how the approach can be used to find specific skills and expertise for a scientific community consisting of people from industry and academia. The proposed approach can be used for the modelling and analysis of various forms of collaboration between and within businesses. As a tool, it could be used for the purposes of strategic networking, to facilitate the creation of project consortia, to identify competitors and other stakeholders in a certain domain, to pinpoint communication channels, to search for specific expertise, or to identify organisational and social structures within organisations.

Keywords

proizvodnja;mreže;analiza mrež;analitika podatkov;profiliranje kompetenc;production;network;network analysis;data analytics;skill profiling;

Data

Language:	English
Year of publishing:	2018
Typology:	1.01 - Original Scientific Article
Organization:	UL FS - Faculty of Mechanical Engineering
UDC:	004.451.5(045)
COBISS:	15977243
ISSN:	0925-5273
Views:	796
Downloads:	720
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary keywords:	proizvodnja;mreže;analiza mrež;analitika podatkov;profiliranje kompetenc;
Pages:	str. 181-191
Issue:	ǂVol. ǂ200
Chronology:	Jun. 2018
DOI:	10.1016/j.ijpe.2018.03.026
ID:	10941839