Harnessing English Sentiment Lexicons for Polarity Detection in Urdu Tweets: A Baseline Approach

It is human instinct to express emotions, and with increasing use of social media, it is more often being expressed through text messages than ever before. The emotions and sentiments encoded in these short text messages are of keen interest to various marketing and advertising agencies. Thus, various lexicons and algorithms have been devised for English, and French language to extract these hidden sentiments. On the other hand, Urdu (or Hindi) the third widely-spoken language in the world [1], lacks any such sentiment lexicons or algorithms. Instead of starting from scratch, we make use of the existing English sentiment lexicons to develop the first sentiment lexicon for Urdu. This lexicon will serve as a baseline for future lexicons developed through more intimate knowledge of Urdu language. Furthermore, we compare its performance with various machine learning (ML) approaches. We also make public the labeled dataset developed by us for Urdu sentiment analysis. We hope that this lexicon and dataset will serve as a benchmark for evaluation of future lexicons and ML approaches for the Urdu language.