Research output: Contribution to journal › Article › peer-review
Big Data Analysis in Social Networks for Managing Risks in Clothing Industry. / Blekanov, Ivan; Krylatov, Alexander; Ivanov, Dmitri; Bubnova, Yulia.
In: IFAC-PapersOnLine, Vol. 52, No. 13, 2019, p. 1710-1714.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Big Data Analysis in Social Networks for Managing Risks in Clothing Industry
AU - Blekanov, Ivan
AU - Krylatov, Alexander
AU - Ivanov, Dmitri
AU - Bubnova, Yulia
PY - 2019
Y1 - 2019
N2 - This paper demonstrates the power of big data analysis of social media for the identification and prioritization of supply chain risks in clothing industry. Due to their high volume, data from social media can be considered a good source for obtaining customer feedback. On the other hand, the high volume of social media data could be efficiently processed solely by special tools for big data analysis. Results of such an analysis include clusters of words, topics and sentiments which allow decision makers to gather negative customer feedback and to manage risks in the distribution of products. A case study in the segment of footwear supply chain was analyzed, where one month of data from Twitter was used. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
AB - This paper demonstrates the power of big data analysis of social media for the identification and prioritization of supply chain risks in clothing industry. Due to their high volume, data from social media can be considered a good source for obtaining customer feedback. On the other hand, the high volume of social media data could be efficiently processed solely by special tools for big data analysis. Results of such an analysis include clusters of words, topics and sentiments which allow decision makers to gather negative customer feedback and to manage risks in the distribution of products. A case study in the segment of footwear supply chain was analyzed, where one month of data from Twitter was used. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
KW - Risk
KW - Supply chain
KW - Big Data
KW - Twitter
KW - Social network
KW - ANALYTICS
KW - RECOVERY
U2 - 10.1016/j.ifacol.2019.11.447
DO - 10.1016/j.ifacol.2019.11.447
M3 - статья
VL - 52
SP - 1710
EP - 1714
JO - IFAC-PapersOnLine
JF - IFAC-PapersOnLine
SN - 2405-8971
IS - 13
Y2 - 28 August 2019 through 30 August 2019
ER -
ID: 50945697