Big data approximations: brand communities and AI

Bowen, Gordon, Okafor, Sebastian, Jamal, Arshad, Dadwal, Sumesh and Jahankhani, Hamid (2023) Big data approximations: brand communities and AI. Interdisciplinary Journal of Economics and Business Law, 12 . pp. 37-57.

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Abstract

The quality of data and information located in brand communities can be ensured by checking for fake reviews or fake information. Artificial intelligence (AI) algorithms have the potential to resolve the ethical issues of fake information and to analyse informational trends accurately and in a timely manner. Thus, the application of AI in brand communities could give firms a sustainable competitive advantage. Also, brand communities extend over many geographical locations, which adds to the richness of the data that could provide valuable insights into products and services. In this application, AI would include an ethical memory and the ability to analyse and synthesise information. Thus, there will be an interface between the algorithm that checks the integrity of the information and the algorithm that analyses the data.

Item Type:	Article
Journal / Publication Title:	Interdisciplinary Journal of Economics and Business Law
Publisher:	CJEAS
ISSN:	2047-8755
Departments:	Institute of Business, Industry and Leadership > Business
Depositing User:	Sebastian Okafor
Date Deposited:	27 Mar 2024 21:04
Last Modified:	14 May 2024 12:01
URI:	https://insight.cumbria.ac.uk/id/eprint/7612

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