Big Data Analysis in Social Networks for Managing Risks in Clothing Industry

Ivan Blekanov, Alexander Krylatov, Dmitri Ivanov, Yulia Bubnova

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)1710-1714
Issue number13
StatePublished - 2019
Event9th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2019 - Berlin, Germany
Duration: 28 Aug 201930 Aug 2019


  • Risk
  • Supply chain
  • Big Data
  • Twitter
  • Social network


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