Reusing test cases across similar applications can significantly reduce testing effort and improve quality. Some recent approaches for automatically reusing Android GUI tests successfully exploit word embedding models to semantically match GUI events across applications. It is a common understanding that word embedding techniques trained on domain-specific corpora perform better on specialized tasks. Our recent study confirms this understanding in the context of test reuse. It shows that word embedding models trained with a corpus of the English descriptions of apps in the Google Play Store lead to a better semantic matching of Android GUI events. Motivated by this result, we hypothesize that we can further increase the effectiveness of semantic matching by partitioning the corpus of app descriptions into domain-specific corpora, obtaining a word embedding model for each domain-specific corpus and selecting the word embedding model most related to the apps considered for a test reuse task. We experimented with 240 configurations built with five general and domain-specific corpora. The experiments do not confirm our hypothesis. This paper sheds light on this unexpected negative result that contradicts the common understanding.