Study of Competition in the Textile Sector by Twitter Social Network Analysis

Abstract

Social networks have become a place where brands or companies are advertised to increase their market share. The companies allocate resources to hire community managers that disseminate quality content and perform customer service tasks. This article presents the development of a tweet retrieval tool and user account information to generate simulation and a strategic analysis of a set of competitors in the Twitter social network during a period of three months. A collection of tweets related to four related textile brands has been obtained. The information retrieval process is done using Python to access the Twitter REST service whose results are indexed using Elasticsearch. Once the data is arranged, Kibana is used to create an interactive panel, with different visualizations, that helps to extract the information hidden in the data, proposing different alternatives, its advantages and its disadvantages.