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 language | English |
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Title of host publication | IET Conference Publications |
Publisher | Institution of Engineering and Technology |
Edition | CP747 |
ISBN (Electronic) | 9781785618161, 9781785618437, 9781785618468, 9781785618871, 9781785619427, 9781785619694, 9781839530036 |
ISBN (Print) | 9781785617911 |
State | Published - 2018 |
Publication series
Name | IET Conference Publications |
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Number | CP747 |
Volume | 2018 |
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