Name: BBN Blog Posts Sentiment Corpus
Description: A random subset of 1200 Levantine dialectal sentences
  chosen from the BBN Arabic-Dialect–English Parallel Text
Provider: Multiple institutions
Paper Title: Sentiment after Translation: A Case-Study on Arabic Social Media Posts
Tasks: sentiment analysis,machine translation
Venue Name: North American Chapter of the Association for Computational Linguistics
Authors: Mohammad Salameh,Saif M. Mohammad,Svetlana Kiritchenko
Abstract: When text is translated from one language into another, sentiment is preserved to varying degrees. In this paper, we use Arabic social media posts as stand-in for source language text, and determine loss in sentiment predictability when they are translated into English, manually and automatically. As benchmarks, we use manually and automatically determined sentiment labels of the Arabic texts. We show that sentiment analysis of English translations of Arabic texts produces competitive results, w.r.t. Arabic sentiment analysis. We discover that even though translation significantly reduces the human ability to recover sentiment, automatic sentiment systems are still able to capture sentiment information from the translations.