From tweets to trends: analyzing sociolinguistic variation and change using the Twitter Corpus of English in Hong Kong (TCOEHK)

Gonzales, Wilkinson Daniel Wong

doi:10.1080/13488678.2023.2251771

Cited by 3 publications

(2 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The investigation of the importance of pragmatic competence in human-AI communication has now become an instrumental field extending beyond the bounds of linguistics and AI toward practical applications in a range of sociolinguistic situations. While sociolinguistic dimensions of the communicative process and cultural significance surrounding the context are stressed by both (Arent et al, 2019;Gonzales, 2023), the latter has not applied his or her approach to communication as a multidirectional and intercommunication phenomenon. It becomes essential for AI systems that are linguistically competent as well as culturally aware, affecting implications on applications in language teaching and therapy (Bartlett, Costescu, Baxter, & Thill, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Linguistic theories and AIs do not define this pragmatic competence exploration in its entirety; the fact is that it is a concern with practical matters. (Arent et al, 2019;Gonzales, 2023) pay significant attention to the socio-linguistic properties of communication, cultural and contextual factors, respectively. Another focus area has been the formation of AI technologies that are not the same as language but also culture-wise with consequences of applications in language learning and therapeutic as discussed in (Tabassum, Rafique, Akram, & Khan, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

An Experimental Analysis of Pragmatic Competence in Human-ChatGPT Conversations

Nazeer,

Khan,

Nawaz

et al. 2024

Pak. J. Humanit. Soc. Sci

View full text Add to dashboard Cite

The main purpose to conduct this research was to evaluate the pragmatic capability of ChatGPT in human interaction and analyze how does ChatGPT, as an advanced language modal, handle linguistic features; irony, metaphor, and indirect requests during conversation with humans. Besides, this study followed a mixed method approach by conducting interactive conversation with three participants to determine the pragmatic competence of ChatGPT through speech act theory and language analysis using irony, metaphor, and indirect requests as linguistics techniques. Thus, ChatGPT has proved to work effectively in human interactions so far by understanding the linguistic context of content and generating responses accordingly yet, it appears more efficient when dealing with tone recognition and complex linguistic constructs like irony and metaphor respectively. To achieve accurate responses in different type of conversations, this research suggests a progressive approach towards the betterment of the responsive capabilities of ChatGPT by incorporating information from various linguistic datasets and users’ feedback.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

An Experimental Analysis of Pragmatic Competence in Human-ChatGPT Conversations

Nazeer,

Khan,

Nawaz

et al. 2024

Pak. J. Humanit. Soc. Sci

View full text Add to dashboard Cite

show abstract

From physical space to cyberspace: Recessive gender biases in social media mirror the real world

Shen,

Ding,

Kong

et al. 2024

Cities

View full text Add to dashboard Cite

Sociolinguistic Analysis with Missing Metadata? Leveraging Linguistic and Semiotic Resources Through Deep Learning to Investigate English Variation and Change on Twitter

Gonzales

2024

Applied Linguistics

View full text Add to dashboard Cite

This paper highlights a language and sign-based computational solution to the problem of missing social metadata on Twitter (now, ‘X’): demographic prediction using Deep Learning. It aims to apply this method to variationist sociolinguistics research, illustrating how the approach can facilitate analyses with missing metadata (i.e. stylistic age and sex/gender) by deriving this metadata solely from publicly available linguistic and semiotic resources on Twitter profiles (e.g. display pictures and biographies). I use my investigations of English tweets from the Philippines and Hong Kong as case examples, examining the extent to which the use of the copula and the use of will-shall modals on social media are conditioned by diachronic factors as well as factors internal and external to language (e.g. social factors). The results reveal the influence of stylistic gender and age as well as other factors on patterns of variation. They offer a glimpse into the nuanced sociolinguistic aspects of language usage on social media, highlighting the advantages of utilizing AI-powered Deep Learning to tackle data-related challenges. The discoveries and methodology hold the possibility of influencing other fields and practical situations beyond the study of language and society.

show abstract

From tweets to trends: analyzing sociolinguistic variation and change using the Twitter Corpus of English in Hong Kong (TCOEHK)

Cited by 3 publications

References 28 publications

An Experimental Analysis of Pragmatic Competence in Human-ChatGPT Conversations

An Experimental Analysis of Pragmatic Competence in Human-ChatGPT Conversations

From physical space to cyberspace: Recessive gender biases in social media mirror the real world

Sociolinguistic Analysis with Missing Metadata? Leveraging Linguistic and Semiotic Resources Through Deep Learning to Investigate English Variation and Change on Twitter

Contact Info

Product

Resources

About