
Social media platforms enable rapid communication, information sharing and opinion expression. However, their misuse of
hate speech targeting race, religion and political differences has become a growing concern. This issue is particularly sensitive
for underrepresented languages like Amharic, a Semitic language with the second-largest number of speakers after Arabic and
the working language of Ethiopia. This study addresses the challenge of detecting hate speech in Amharic text by analyzing
posts and comments from Facebook, YouTube and Twitter. A dataset of 7,590 labelled entries was collected using the Face Pager
tool, focusing on hate speech related to race, religion, politics and neutral content.