Managing extracted knowledge from big social media data for business decision making

TLDR

The study proposes a knowledge‑management framework that integrates Big Data, social media, and KM systems to extract and compare competitor knowledge from large‑scale Twitter data, providing practical guidance for organizations. The authors conducted a case study of almost one million Twitter messages from five major retailers, extracting and comparing competitor knowledge to generate actionable business insights. The framework proved effective, offering visually presented, competitor‑based insights that support business intelligence and decision making, marking a pioneering use of Big Data to extract social media knowledge.

Abstract

Purpose This paper aims to propose a knowledge management (KM) framework for leveraging big social media data to help interested organizations integrate Big Data technology, social media and KM systems to store, share and leverage their social media data. Specifically, this research focuses on extracting valuable knowledge on social media by contextually comparing social media knowledge among competitors. Design/methodology/approach A case study was conducted to analyze nearly one million Twitter messages associated with five large companies in the retail industry (Costco, Walmart, Kmart, Kohl’s and The Home Depot) to extract and generate new knowledge and to derive business decisions from big social media data. Findings This case study confirms that this proposed framework is sensible and useful in terms of integrating Big Data technology, social media and KM in a cohesive way to design a KM system and its process. Extracted knowledge is presented visually in a variety of ways to discover business intelligence. Originality/value Practical guidance for integrating Big Data, social media and KM is scarce. This proposed framework is a pioneering effort in using Big Data technologies to extract valuable knowledge on social media and discover business intelligence by contextually comparing social media knowledge among competitors.