Social media competitive intelligence: measurement and visualization from a higher education organization

Abstract

Competitive Intelligence (CI) is a valuable tool that allows organizations to have information relevant to their environment, allowing them to anticipate changes, identify opportunities and focus on innovation. Implement useful methods for the control and systematic monitoring of the impact generated in social networks, is very useful in the context of the CI. This article proposes a methodology designed to process the information obtained about the activity of various Twitter accounts linked to the same institution. The first analysis, based on structured data of the twitters, lets to identify graphically how to find relations between the accounts data over the time. After that, it is presented how Natural Language Processing (NLP) using machine learning techniques could be used to visualize, classify and group the information. The methodology was tested with public data from a university through cloud computing services, so an CI analysis is performed for the institution. As result, we found the identification of crucial discussion topics within the analyzed community is highlighted, as well as the proposal of a control panel for monitoring the various associated accounts.