  Recent years have seen a rise in interest for cross-lingual transfer between
languages with similar typology, and between languages of various scripts.
However, the interplay between language similarity and difference in script on
cross-lingual transfer is a less studied problem. We explore this interplay on
cross-lingual transfer for two supervised tasks, namely part-of-speech tagging
and sentiment analysis. We introduce a newly annotated corpus of Algerian
user-generated comments comprising parallel annotations of Algerian written in
Latin, Arabic, and code-switched scripts, as well as annotations for sentiment
and topic categories. We perform baseline experiments by fine-tuning
multi-lingual language models. We further explore the effect of script vs.
language similarity in cross-lingual transfer by fine-tuning multi-lingual
models on languages which are a) typologically distinct, but use the same
script, b) typologically similar, but use a distinct script, or c) are
typologically similar and use the same script. We find there is a delicate
relationship between script and typology for part-of-speech, while sentiment
analysis is less sensitive.
