Social sensing applications and case study using acoustic Arabic opinion mining

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Recently social sensing has gained a growing attention with many promising applications in smart cities. This paper reviews application domains of social sensing to provide context-aware services in smart cities including healthcare, wellness and safety, transportation, business, and environmental monitoring. Moreover, a case study is presented to understand human opinions expressed in Arabic spontaneous speech. Thirty four features are extracted to discriminate each opinion from audio signals and several machine-learning classifiers are applied to detect its polarity. To deal with a real-world problem, the dataset is composed of audio clips with diverse characteristics including speakers’ nationalities and ages, environments and topics.

Original languageEnglish
Title of host publicationIET Conference Publications
PublisherInstitution of Engineering and Technology
EditionCP747
ISBN (Electronic)9781785618161, 9781785618437, 9781785618468, 9781785618871, 9781785619427, 9781785619694, 9781839530036
ISBN (Print)9781785617911
StatePublished - 2018

Publication series

NameIET Conference Publications
NumberCP747
Volume2018

Bibliographical note

Publisher Copyright:
© 2018 Institution of Engineering and Technology. All rights reserved.

Keywords

  • Arabic
  • Audio opinion mining
  • Big data
  • Classification
  • Smart cities
  • Social networks
  • Social sensing

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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