The Small World of Singlish Words is our lab’s ongoing efforts to develop psycholinguistic research resources for Singapore English. Singapore English is known for its unique vocabulary of words like shiok, diam, sian, and chope. But unfortunately we don’t have much lexical information for these words.
In this project, we collected affective-semantic ratings for a set of 283 Singlish words and concepts from native speakers of Singapore English. You can think of these ratings as your emotional or mental responses when viewing a Singlish concept. For instance, the word shiok elicits highly positive, arousing emotions, but is not a particularly concrete or funny concept. In contrast, Singaporeans find the word botak to be highly concrete and funny :)
These data can be used for inferring sentiment of text or language generated by Singapore English speakers which can have various natural language processing applications in industry.
In a different project, we are also collecting word associations for uniquely Singaporean words and concepts so that we can build the first cognitive language network of Singapore English words. Here is a rudimentary network of the word “shiok”.
If you consider yourself a native speaker of Singapore English, we would like to invite you to participate in our citizen science research study. Simply click here and begin! Thank you in advance for your contributions to science :)
If you would like to receive updates about the project, drop us an email at singlishwords@nus.edu.sg, or check out our social media pages below:
Facebook | Twitter | Project Page
We would like to thank [X] for helping us process the definitions featured on this visualization application.
Our research is funded by the Social Science Research Council of Singapore (MOE 2021-SSHR-003; Project title: “Measuring the Singaporean Mental Lexicon: Lexical-semantic norms for Singapore English words”).
Source code for this application can be found on Github.
More information about the methodology involved in developing the data featured in this application can be found in our preprint, and the raw data can be downloaded in the ‘Table’ tab or at our OSF page.