The linguistic landscape of tourist attractions in Singapore
This paper explores the linguistic landscape of Singapore’s tourist attractions by observing the languages present on signs at eight different tourist attractions. By taking photographs of signs at the tourist attractions, this study aimed to investigate the languages present and whether the lang...
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2020
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sg-ntu-dr.10356-1382832020-04-30T04:49:46Z The linguistic landscape of tourist attractions in Singapore Teo, Boon Yong Perono Cacciafoco Francesco School of Humanities fcacciafoco@ntu.edu.sg Humanities::Linguistics::Sociolinguistics This paper explores the linguistic landscape of Singapore’s tourist attractions by observing the languages present on signs at eight different tourist attractions. By taking photographs of signs at the tourist attractions, this study aimed to investigate the languages present and whether the languages on signs reflect the nationality of tourists visiting them. Top-down and bottom-up signs were compared in terms of both languages present as well as code preference. This paper also explored the commodification of language in Singapore’s tourist attractions. Results showed that the languages on signs at a few tourist attractions did reflect the nationality of tourists who visited them, but also that exclusion of the languages did not mean that the number of tourists visiting from certain countries was low. A few differences between top-down and bottom-up signs were observed, including differences in code preference of signs in Chinatown and also the low percentage of Malay and Tamil on bottom-up signs in Chinatown compared to top-down ones. Chinese and Tamil can be seen to have been commodified in Chinatown and Little India respectively, in order to give tourists a more authentic experience of the two attractions. Bachelor of Arts in Linguistics and Multilingual Studies 2020-04-30T03:35:04Z 2020-04-30T03:35:04Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/138283 en application/pdf Nanyang Technological University |
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Humanities::Linguistics::Sociolinguistics Teo, Boon Yong The linguistic landscape of tourist attractions in Singapore |
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This paper explores the linguistic landscape of Singapore’s tourist attractions by observing the
languages present on signs at eight different tourist attractions. By taking photographs of signs
at the tourist attractions, this study aimed to investigate the languages present and whether the
languages on signs reflect the nationality of tourists visiting them. Top-down and bottom-up
signs were compared in terms of both languages present as well as code preference. This paper
also explored the commodification of language in Singapore’s tourist attractions. Results
showed that the languages on signs at a few tourist attractions did reflect the nationality of
tourists who visited them, but also that exclusion of the languages did not mean that the number
of tourists visiting from certain countries was low. A few differences between top-down and
bottom-up signs were observed, including differences in code preference of signs in Chinatown
and also the low percentage of Malay and Tamil on bottom-up signs in Chinatown compared
to top-down ones. Chinese and Tamil can be seen to have been commodified in Chinatown and
Little India respectively, in order to give tourists a more authentic experience of the two
attractions. |
author2 |
Perono Cacciafoco Francesco |
author_facet |
Perono Cacciafoco Francesco Teo, Boon Yong |
format |
Final Year Project |
author |
Teo, Boon Yong |
author_sort |
Teo, Boon Yong |
title |
The linguistic landscape of tourist attractions in Singapore |
title_short |
The linguistic landscape of tourist attractions in Singapore |
title_full |
The linguistic landscape of tourist attractions in Singapore |
title_fullStr |
The linguistic landscape of tourist attractions in Singapore |
title_full_unstemmed |
The linguistic landscape of tourist attractions in Singapore |
title_sort |
linguistic landscape of tourist attractions in singapore |
publisher |
Nanyang Technological University |
publishDate |
2020 |
url |
https://hdl.handle.net/10356/138283 |
_version_ |
1681057221791711232 |