## 4 Results
### Statistical Analysis of Datasets  
Our statistical analyses provided further insights into the characteristics of the generated datasets, specifically addressing our research question on the influence of region-specific prompts on linguistic diversity. The frequent term analysis revealed how varying levels of prompting, as well as the different regional contexts, elicit more unique and regionally specific vocabulary. Table 2 presents the top-20 most frequent words from the different synthetic datasets, highlighting several unique terms that appear to be generated as a result of the different regional prompts. One of the key observations is that the datasets generated from more detailed prompts exhibit a higher proportion of specialized or domain-specific terms, even within the top-20 most frequent words. This suggests that the regional prompts successfully captured and emphasized the unique linguistic characteristics of each region. This finding further \begin{table}
\begin{tabular}{l l l l l l l} \hline \hline \multirow{2}{*}{**Baseline**} & \multicolumn{3}{c}{**Regional General**} & \multicolumn{3}{c}{**Regional Detailed**} \\ \cline{2-7}  & **US** & **UK** & **IN** & **US\_2** & **UK\_2** & **IN\_2** \\ \hline feeling & feeling & feeling & feeling & like & _proper_ & feeling \\ \hline love & love & absolutely & love & just & feeling & just \\ \hline today & today & love & _india_ & feeling & just & like \\ \hline life & grateful & today & today & today & _cluffed_ & yaar \\ \hline absolutely & life & _uk_ & absolutely & right & _mate_ & today \\ \hline grateful & believe & life & let & life & like & _chai_ \\ \hline believe & absolutely & grateful & sending & got & absolutely & time \\ \hline spread & right & believe & believe & believe & believe & life \\ \hline fear & joyful & just & grateful & _vibes_ & right & believe \\ \hline sadness & time & right & time & _shook_ & today & _bollywood_ \\ \hline right & let & sending & life & good & _gutted_ & totally \\ \hline time & _spread_ & _fuming_ & stay & _blessed_ & _cuppa_ & _movie_ \\ \hline remember & world & bit & knows & _feelin_ & time & _hai_ \\ \hline joyful & scared & people & _staystrong_ & _bummed_ & bits & world \\ \hline just & stay & okay & times & deal & _mates_ & _kya_ \\ \hline wow & just & _chuffed_ & _boundaries_ & living & _imit_ & _vibe_ \\ \hline let & times & _spooked_ & spread & best & _ve_ & _boss_ \\ \hline okay & support & remember & support & ride & _fuming_ & _desi_ \\ \hline spreadlove & staystrong & _blimey_ & fear & time & life & shake \\ \hline unexpected & way & throws & just & love & _blimey_ & _nailed_ \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Top-20 words by frequency for the generated synthetic datasets. supports the hypothesis that more detailed prompts lead to richer and more diverse word usage. In the case of the regional detailed dataset for English from the United States, the use of slang and colloquial expressions, such as \"vibes\", \"shook\", and \"feelin\" can be observed. These terms reflect the informal, conversational nature of the language in this region. Similarly, the regional detailed dataset from the United Kingdom includes vocabulary that is distinctly British, such as \"mates\", \"gutted\", and \"innit\", among others. This confirms the presence of region-specific linguistic features that distinguish British English from other variants of the language. Moreover, the dataset from India reveals a fascinating mix of cultural cues, with terms such as \"Bollywood\" and \"chai\" commonly appearing. Additionally, this dataset contains numerous instances of code-switching, where English is mixed with local languages. Terms like \"yaar\", \"hai\", and \"kia\" are indicative of the multilingual nature of communication in this region, where speakers frequently incorporate words from Hindi, Urdu, and other regional languages into their English discourse.