  Sentiment analysis has been an active area of research in the past two
decades and recently, with the advent of social media, there has been an
increasing demand for sentiment analysis on social media texts. Since the
social media texts are not in one language and are largely code-mixed in
nature, the traditional sentiment classification models fail to produce
acceptable results. This paper tries to solve this very research problem and
uses bi-directional LSTMs along with language tagging, to facilitate sentiment
tagging of code-mixed Tamil texts that have been extracted from social media.
The presented algorithm, when evaluated on the test data, garnered precision,
recall, and F1 scores of 0.59, 0.66, and 0.58 respectively.
