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The ever-increasing application of computer and internet mandates a longer domain for computer-mediated-communication (CMC). Internet chat as a principal feature of CMC has attracted tremendous attention among the youths in recent years.  Thus, this study has focused on the written chats of 100 Iranian university students majoring in different disciplines. We analyzed 400 chat samples (composed of 4000 moves) in terms of opening and continuing speech functions based on Eggins and Slade’s (1997) model of casual conversation. We also examined humor and paralinguistic features based on taxonomies of Huffaker and Calvert (2005) and Nastri, Peña, and Hancock (2006). Among the various types of speech functions, nine opening speech functions, seven continuing speech functions and four humor and paralinguistic features were investigated. The analysis of the data shows that the salient opening speech function has been ‘statement: opinion’ which provides attitudinal and evaluative information. Additionally, the outstanding types of continuing speech functions are ‘prolong: extend’, ‘prolong: enhance’, and ‘append: elaborate’. Therefore, it is in order for the participants to offer additional or contrasting information to the previous move or qualify it by giving details of time, place, condition, etc. Moreover, in case of interruption by the other chatter, the participants mostly tend to clarify, exemplify or reiterate the previous move. Furthermore, the participants produced irony, as a humorous element, in a great volume which is indicative of their tendency toward being indirect during conversation. The subjects also used many paralinguistic features such as misspellings and repeated punctuations in order to express their emotions and attract their partners’ attention in the absence of verbal communication.

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This study investigates syntactic and thematic strategies by a translation model based on artificial intelligence, ChatGPT, in English to Persian literary translation. Mona Baker's (2011) theory of linear dislocation aims to assess whether and to what extent four major strategies (voice change, verb change, nominalization, and extraposition) occur in AI-generated text. The data set includes Thomas Hardy's short story Absent Mindedness in a Parish Choir and its full Persian translation produced by ChatGPT. A qualitative comparative method was adopted, in which Baker's scheme was taken as the starting point for text analysis. Forty four segments were identified and examined, each demonstrating the use of at least one of the mentioned strategies. The findings show that ChatGPT makes considerable use of all four strategies implicitly: verb change (31.82%), voice change (27.27%), nominalization (22.73%), and extraposition (18.18%). These results preserved thematic structure and communicative coherence in most cases. The study identifies ChatGPT's capacity to respond to functional translation in literary translation with idiomatic, rhythmic, and rhetorical fidelity. It suggests Baker's strategies are still relevant not only for human translators but also as a valuable instrument for evaluating and post-editing AI translations, especially literature. This study investigates syntactic and thematic strategies by a translation model based on artificial intelligence, ChatGPT, in English to Persian literary translation. Mona Baker's (2011) theory of linear dislocation aims to assess whether and to what extent four major strategies (voice change, verb change, nominalization, and extraposition) occur in AI-generated text. The data set includes Thomas Hardy's short story Absent Mindedness in a Parish Choir and its full Persian translation produced by ChatGPT. A qualitative comparative method was adopted, in which Baker's scheme was taken as the starting point for text analysis. Forty four segments were identified and examined, each demonstrating the use of at least one of the mentioned strategies. The findings show that ChatGPT makes considerable use of all four strategies implicitly: verb change (31.82%), voice change (27.27%), nominalization (22.73%), and extraposition (18.18%). These results preserved thematic structure and communicative coherence in most cases. The study identifies ChatGPT's capacity to respond to functional translation in literary translation with idiomatic, rhythmic, and rhetorical fidelity. It suggests Baker's strategies are still relevant not only for human translators but also as a valuable instrument for evaluating and post-editing AI translations, especially literature.