Africa is home to over 2,000 languages from more than six language families and has the
highest linguistic diversity among all continents. These include 75 languages with at least …

This paper presents the study of sentiment analysis for Amharic social media texts. As the
number of social media users is ever-increasing, social media platforms would like to …

Online social media platforms such as YouTube have a wide, global reach. However, little is
known about the experience of low-resourced language speakers on such platforms; …

Automatic identification of offensive/abusive language is very necessary to get rid of
unwanted behavior. However, it is more challenging to generalize the solution due to the …

In this paper, we present a study of efficient data selection and annotation strategies for
Amharic hate speech. We also build various classification models and investigate the …

Hate speech is a growing problem on social media. It can seriously impact society,
especially in countries like Ethiopia, where it can trigger conflicts among diverse ethnic and …

This paper presents an Amharic hate speech annotation using the Yandex Toloka
crowdsourcing platform. The dataset for this paper is collected from 5 consecutive years in …

The prevalence of digital media and evolving sociopolitical dynamics have significantly
amplified the dissemination of hateful content. Existing studies mainly focus on classifying …

Accepted: 16 March 2022 As the number of social media comments available online grows,
the spread of hate speech has grown gradually. When someone uses hate speech as a …

In contemporary society, the proliferation of hate speech is increasingly prevalent across
various social media platforms, with a notable trend of incorporating memes to amplify its …