The variability of adverbial placement in the modified infinitive construction (i.e. split infinitives vs. full infinitives with adverbial pre- and post-modification) has been widely discussed in the (American English) literature. Yet a convincing generalized explanation for the variation that simultaneously incorporates language-internal and language-external factors has yet to be found, particularly in English varieties that have not received as much scholarly attention as standardized varieties. This article investigates modified infinitive syntactic variation in Twitter-style Philippine English (PhE) using a 135-million-word Twitter corpus. It adopts a Bayesian approach in conducting a multiple multinomial regression analysis of the said variation, with the help of Deep-Learning-based demographic inference tools. Although the conditioning effects of some factors diverge from patterns discussed in prior work, the results generally show that language-internal (e.g. stress and rhythm, adverb type, adverb length) and language-external factors (i.e. time, age, sex, geography) jointly shape the choice to split the infinitive in this linguistic style of PhE.