Evaluating noise perception through online social networks: A text mining approach to design a noise-event alarm system based on social media content

Gascó Sánchez, Luis and Asensio Rivera, César and Arcas Castro, Guillermo de and Clavel, Chloe (2019). Evaluating noise perception through online social networks: A text mining approach to design a noise-event alarm system based on social media content. In: "Inter Noise 2019: Noise control for a better environment", 16 al 19 de junio de 2019, Madrid (España). pp. 1-12.

Description

Title: Evaluating noise perception through online social networks: A text mining approach to design a noise-event alarm system based on social media content
Author/s:
  • Gascó Sánchez, Luis
  • Asensio Rivera, César
  • Arcas Castro, Guillermo de
  • Clavel, Chloe
Item Type: Presentation at Congress or Conference (Article)
Event Title: Inter Noise 2019: Noise control for a better environment
Event Dates: 16 al 19 de junio de 2019
Event Location: Madrid (España)
Title of Book: Proceedings of Internoise 2019
Date: 2019
Subjects:
Freetext Keywords: Text mining; Community engagement; Noise annoyance; Machine Learning; NLP
Faculty: E.T.S.I. y Sistemas de Telecomunicación (UPM)
Department: Teoría de la Señal y Comunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

With the rapid rise of the use of Online Social Networks, people have been sharing their opinions and feelings on the Internet: they write about their personal interests and political opinions, but also about their feelings about noisy activities and sounds they hear during their daily life. This textual information could provide policy makers and city managers with insights about the community response towards specific noisy events in cities that may be useful for improving the management of these activities. In this paper, we present a methodology to analyze automatically these Internet opinions by using machine learning and Natural Language processing Technologies. This approach has allowed us to build a system that automatically detects and classifies noise complaints by source, using texts written on online social networks as input. We also present a noise-event alarm system based on statistical process control theory that uses the power of our methodology to detect problematic noise events, as well as the reason why those events caused annoyance to population.

More information

Item ID: 64986
DC Identifier: https://oa.upm.es/64986/
OAI Identifier: oai:oa.upm.es:64986
Official URL: http://www.sea-acustica.es/fileadmin/INTERNOISE_2019/Enter.htm
Deposited by: Memoria Investigacion
Deposited on: 08 Feb 2021 11:22
Last Modified: 08 Feb 2021 11:22
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