Sodiq179/Sentiment_Analysis_for_Tunisian_Arabizi

This repository holds some NLP models for classifying sentiment in the Tunisian Arabizi dialect # Sentiment_Analysis_for_Tunisian_Arabizi This repository holds some NLP models for classifying sentiment in the Tunisian Arabizi dialect ## Description On social media, Arabic speakers tend to express themselves in their own local dialect. To do so, Tunisians use ‘Tunisian Arabizi’, where the Latin alphabet is supplemented with numbers. However, annotated datasets for Arabizi are limited; in fact, this challenge uses the only known Tunisian Arabizi dataset in existence. Sentiment analysis relies on multiple word senses and cultural knowledge, and can be influenced by age, gender and socio-economic status.For this task, we have collected and annotated sentences from different social media platforms. The objective of this challenge is to, given a sentence, classify whether the sentence is of positive, negative, or neutral sentiment. For messages conveying both a positive and negative sentiment, whichever is the stronger sentiment should be chosen. Predict if the text would be considered positive, negative, or neutral (for an average user). This is a binary task. Such solutions could be used by banking, insurance companies, or social media influencers to better understand and interpret a product’s audience and their reactions. ## Evaluation The metric for the classification tasks will be Accuracy. ## Models Description