1 September 2022, by Dr. Seid Muhie Yimam
LT Group, in collaboration with Masakhane, HausaNLP (Nigeria), ICT4D Research group (Ethiopia), and other researchers working on low-resource NLP, will organize the first AfriSenti-SemEval shared task (Task 12).
The AfriSenti-SemEval Shared Task 12 is based on a collection of Twitter datasets in 13 African languages for sentiment classification. It consists of three sub-tasks. Participants can select one or more tasks depending on their preference.
Task A: Monolingual Sentiment Classification
Given training data in a target language, determine the polarity of a tweet in the target language (positive, negative, or neutral). If a tweet For messages conveying both a positive and negative sentiment, whichever is the stronger sentiment should be chosen.
Task B: Multilingual Sentiment Classification
Given a combined training data from 10 African languages, determine the polarity of a tweet in the target language (positive, negative, or neutral)
Task C: Zero-Shot Sentiment Classification
Given unlabeled tweets in two African languages (Tigrinya and Kinyarwanda), leverage any or all of the available training datasets in Subtasks 1 and 2 to determine the sentiment of a tweet in the two target languages is positive, negative, or neutral.