Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/50145

Automatically Quantifying Customer Need Tweets: Towards a Supervised Machine Learning Approach

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Item Summary

Title:Automatically Quantifying Customer Need Tweets: Towards a Supervised Machine Learning Approach
Authors:Kühl, Niklas
Mühlthaler, Marius
Goutier, Marc
Keywords:Social Information Systems
automated need elicitation, customer needs, e-mobility, supervised machine learning, twitter
Date Issued:03 Jan 2018
Abstract:The elicitation of customer needs is an important task for businesses in order to design customer-centric products and services. While there are different approaches available, most lack automation, scalability and monitoring capabilities. In this work, we demonstrate the feasibility to automatically identify and quantify customer needs by training and evaluating on previously-labeled Twitter data. To achieve that, we utilize a supervised machine learning approach. Our results show that the classification performances are statistically superior-”but can be further improved in the future.
Pages/Duration:10 pages
URI/DOI:http://hdl.handle.net/10125/50145
ISBN:978-0-9981331-1-9
DOI:10.24251/HICSS.2018.258
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Social Information Systems


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