  Sentiment analysis, also called opinion mining, is the field of study that
analyzes people's opinions,sentiments, attitudes and emotions. Songs are
important to sentiment analysis since the songs and mood are mutually dependent
on each other. Based on the selected song it becomes easy to find the mood of
the listener, in future it can be used for recommendation. The song lyric is a
rich source of datasets containing words that are helpful in analysis and
classification of sentiments generated from it. Now a days we observe a lot of
inter-sentential and intra-sentential code-mixing in songs which has a varying
impact on audience. To study this impact we created a Telugu songs dataset
which contained both Telugu-English code-mixed and pure Telugu songs. In this
paper, we classify the songs based on its arousal as exciting or non-exciting.
We develop a language identification tool and introduce code-mixing features
obtained from it as additional features. Our system with these additional
features attains 4-5% accuracy greater than traditional approaches on our
dataset.
