  The scarcity of available text corpora for low-resource languages like
Albanian is a serious hurdle for research in natural language processing tasks.
This paper introduces AlbNews, a collection of 600 topically labeled news
headlines and 2600 unlabeled ones in Albanian. The data can be freely used for
conducting topic modeling research. We report the initial classification scores
of some traditional machine learning classifiers trained with the AlbNews
samples. These results show that basic models outrun the ensemble learning ones
and can serve as a baseline for future experiments.
