Twitter Sentiment Analysis-2 : Dhoom3 Movie

Aim

Analyzing positive and negative sentiments of people towards newly released Amir Khan, Abhishek Bacchan and Katerina Kaif starer ‘DHOOM3’ movie.

Method

To analyze public sentiment we have used Twitter as our test bed. The movie released on 20^th December therefore we take the 20^th December to 28^th December as our analysis window.

We used the Twitter API with Python interface to extract public tweets with a list of key word –

Dhoom3, #Dhoom3, @Dhoom3TheMovie, Dhoom:3

We have trained a Naïve Bayes classifier over 18 negative sentiment tweets and 18 positive sentiment tweets. This classifier is then used to classify above mentioned tweets into positive and negative sentiment tweets.

Results

	#PositiveSentimentTweets	#NegativeSentimentTweets	%Positive
20 Dec 2013 - 28 Dec 2013	2603	108	96.01

Limitations

1. Twitter is used by relatively smaller population compared to facebook and therefore extracts the view of this group.
2. The analysis only used tweets in English language. Hindi and local languages haven’t been analyzed.
3. Analysis of tweets is also limited by query terms used by us which only 4 terms found by us through manual tweet observations.
4. Due to multiple tags used for search there are a few duplicate tweets that can be both positive or negative.
5. Some of the tweets are related to money collection of the movie which are classified as positive.
6. This is a binary classification and therefore many neutral tweets may be classified in either positive or negative.