Utilizing Elbow Method for Text Clustering Optimization in Analyzing Social Media Marketing Content of Indonesian e-Commerce
The massive increases in textual data from Twitter and text analytics simultaneously have driven organizations to obtain hidden insights to implement the proper marketing strategies for businesses. The vast information generated by Twitter enables most e-commerce businesses to utilize Twitter to imp...
Main Authors: | , , |
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Format: | Article |
Language: | English |
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Petra Christian University
2021-12-01
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Series: | Jurnal Teknik Industri |
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author | Aisyah Larasati Raretha Maren Retno Wulandari |
author_facet | Aisyah Larasati Raretha Maren Retno Wulandari |
author_sort | Aisyah Larasati |
collection | DOAJ |
description | The massive increases in textual data from Twitter and text analytics simultaneously have driven organizations to obtain hidden insights to implement the proper marketing strategies for businesses. The vast information generated by Twitter enables most e-commerce businesses to utilize Twitter to implement social media marketing. One of those e-commerce businesses is Blibli Indonesia. Intense business competition has led them to perform marketing strategies to understand consumer tendencies. Focusing the marketing strategies on consumer preferences enables the increase of consumer interest in Blibli, which is in line with enhancing the opportunity to reach new consumers. This research aims to discover Twitter content based on k-means results to cluster the tweets of @bliblidotcom. The best cluster is determined with the elbow method by selecting the deepest curvature, three clusters. The result suggests that Twitter users like Park Seo Jun's content. Hence, Blibli can focus on that content as its business marketing strategy on the Twitter platform. |
first_indexed | 2024-04-12T15:47:31Z |
format | Article |
id | doaj.art-791f15e7f80949748dc4dbebadfd3d73 |
institution | Directory Open Access Journal |
issn | 1411-2485 |
language | English |
last_indexed | 2024-04-12T15:47:31Z |
publishDate | 2021-12-01 |
publisher | Petra Christian University |
record_format | Article |
series | Jurnal Teknik Industri |
spelling | doaj.art-791f15e7f80949748dc4dbebadfd3d732022-12-22T03:26:37ZengPetra Christian UniversityJurnal Teknik Industri1411-24852021-12-01232111120https://doi.org/10.9744/jti.23.2.111-120Utilizing Elbow Method for Text Clustering Optimization in Analyzing Social Media Marketing Content of Indonesian e-CommerceAisyah Larasati0Raretha Maren1Retno Wulandari2State University of MalangState University of MalangState University of MalangThe massive increases in textual data from Twitter and text analytics simultaneously have driven organizations to obtain hidden insights to implement the proper marketing strategies for businesses. The vast information generated by Twitter enables most e-commerce businesses to utilize Twitter to implement social media marketing. One of those e-commerce businesses is Blibli Indonesia. Intense business competition has led them to perform marketing strategies to understand consumer tendencies. Focusing the marketing strategies on consumer preferences enables the increase of consumer interest in Blibli, which is in line with enhancing the opportunity to reach new consumers. This research aims to discover Twitter content based on k-means results to cluster the tweets of @bliblidotcom. The best cluster is determined with the elbow method by selecting the deepest curvature, three clusters. The result suggests that Twitter users like Park Seo Jun's content. Hence, Blibli can focus on that content as its business marketing strategy on the Twitter platform.e-commercetwittermarketingtext miningk-meanselbow |
spellingShingle | Aisyah Larasati Raretha Maren Retno Wulandari Utilizing Elbow Method for Text Clustering Optimization in Analyzing Social Media Marketing Content of Indonesian e-Commerce Jurnal Teknik Industri e-commerce marketing text mining k-means elbow |
title | Utilizing Elbow Method for Text Clustering Optimization in Analyzing Social Media Marketing Content of Indonesian e-Commerce |
title_full | Utilizing Elbow Method for Text Clustering Optimization in Analyzing Social Media Marketing Content of Indonesian e-Commerce |
title_fullStr | Utilizing Elbow Method for Text Clustering Optimization in Analyzing Social Media Marketing Content of Indonesian e-Commerce |
title_full_unstemmed | Utilizing Elbow Method for Text Clustering Optimization in Analyzing Social Media Marketing Content of Indonesian e-Commerce |
title_short | Utilizing Elbow Method for Text Clustering Optimization in Analyzing Social Media Marketing Content of Indonesian e-Commerce |
title_sort | utilizing elbow method for text clustering optimization in analyzing social media marketing content of indonesian e commerce |
topic | e-commerce marketing text mining k-means elbow |
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