The disruptometer: an artificial intelligence algorithm for market insights

Social media data mining is rapidly developing to be a mainstream tool for marketing insights in today’s world, due to the abundance of data and often freely accessed information. In this paper, we propose a framework for market research purposes called the Disruptometer. The algorithm uses keywords...

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Main Authors:	Wan Nordin, Mimi Aminah, Vedenyapin, Dmitry, Alghifari, Muhammad Fahreza, Gunawan, Teddy Surya
Format:	Article
Language:	English English
Published:	Universitas Ahmad Dahlan in collaboration with IAES Indonesia Section 2019
Subjects:	TK7885 Computer engineering
Online Access:	http://irep.iium.edu.my/73880/ http://irep.iium.edu.my/73880/ http://irep.iium.edu.my/73880/ http://irep.iium.edu.my/73880/1/73880_The%20Disruptometer-%20An%20Artificial%20Intelligence.pdf http://irep.iium.edu.my/73880/7/73880_The%20disruptometer-An%20artificial%20intelligence%20algorithm%20for%20market%20insights_Scopus.pdf

id	iium-73880
recordtype	eprints
spelling	iium-738802019-11-24T12:01:35Z http://irep.iium.edu.my/73880/ The disruptometer: an artificial intelligence algorithm for market insights Wan Nordin, Mimi Aminah Vedenyapin, Dmitry Alghifari, Muhammad Fahreza Gunawan, Teddy Surya TK7885 Computer engineering Social media data mining is rapidly developing to be a mainstream tool for marketing insights in today’s world, due to the abundance of data and often freely accessed information. In this paper, we propose a framework for market research purposes called the Disruptometer. The algorithm uses keywords to provide different types of market insights from data crawling. The preliminary algorithm data-mines information from Twitter and outputs 2 parameters – Product-to-Market Fit and Disruption Quotient, which is obtained from a brand’s customer value proposition, problem space, and incumbent space. The algorithm has been tested with a venture capitalist portfolio company and market research firm to show high correlated results. Out of 4 brand use cases, 3 obtained identical results with the analysts ‘studies. Universitas Ahmad Dahlan in collaboration with IAES Indonesia Section 2019-09 Article PeerReviewed application/pdf en http://irep.iium.edu.my/73880/1/73880_The%20Disruptometer-%20An%20Artificial%20Intelligence.pdf application/pdf en http://irep.iium.edu.my/73880/7/73880_The%20disruptometer-An%20artificial%20intelligence%20algorithm%20for%20market%20insights_Scopus.pdf Wan Nordin, Mimi Aminah and Vedenyapin, Dmitry and Alghifari, Muhammad Fahreza and Gunawan, Teddy Surya (2019) The disruptometer: an artificial intelligence algorithm for market insights. Bulletin of Electrical Engineering and Informatics, 8 (2). pp. 727-734. ISSN 2302-9285 E-ISSN 2302-9285 http://www.beei.org/index.php/EEI/article/view/1494/1084 10.11591/eei.v8i2.1494
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK7885 Computer engineering
spellingShingle	TK7885 Computer engineering Wan Nordin, Mimi Aminah Vedenyapin, Dmitry Alghifari, Muhammad Fahreza Gunawan, Teddy Surya The disruptometer: an artificial intelligence algorithm for market insights
description	Social media data mining is rapidly developing to be a mainstream tool for marketing insights in today’s world, due to the abundance of data and often freely accessed information. In this paper, we propose a framework for market research purposes called the Disruptometer. The algorithm uses keywords to provide different types of market insights from data crawling. The preliminary algorithm data-mines information from Twitter and outputs 2 parameters – Product-to-Market Fit and Disruption Quotient, which is obtained from a brand’s customer value proposition, problem space, and incumbent space. The algorithm has been tested with a venture capitalist portfolio company and market research firm to show high correlated results. Out of 4 brand use cases, 3 obtained identical results with the analysts ‘studies.
format	Article
author	Wan Nordin, Mimi Aminah Vedenyapin, Dmitry Alghifari, Muhammad Fahreza Gunawan, Teddy Surya
author_facet	Wan Nordin, Mimi Aminah Vedenyapin, Dmitry Alghifari, Muhammad Fahreza Gunawan, Teddy Surya
author_sort	Wan Nordin, Mimi Aminah
title	The disruptometer: an artificial intelligence algorithm for market insights
title_short	The disruptometer: an artificial intelligence algorithm for market insights
title_full	The disruptometer: an artificial intelligence algorithm for market insights
title_fullStr	The disruptometer: an artificial intelligence algorithm for market insights
title_full_unstemmed	The disruptometer: an artificial intelligence algorithm for market insights
title_sort	disruptometer: an artificial intelligence algorithm for market insights
publisher	Universitas Ahmad Dahlan in collaboration with IAES Indonesia Section
publishDate	2019
url	http://irep.iium.edu.my/73880/ http://irep.iium.edu.my/73880/ http://irep.iium.edu.my/73880/ http://irep.iium.edu.my/73880/1/73880_The%20Disruptometer-%20An%20Artificial%20Intelligence.pdf http://irep.iium.edu.my/73880/7/73880_The%20disruptometer-An%20artificial%20intelligence%20algorithm%20for%20market%20insights_Scopus.pdf
first_indexed	2023-09-18T21:44:45Z
last_indexed	2023-09-18T21:44:45Z
_version_	1777413375289982976

The disruptometer: an artificial intelligence algorithm for market insights

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