sentiment analytics
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TEXT ANALYTICS
Analysis of reviews fetched from IMDB for Hobbit Series
Submitted By :-Amrapalli KaranKamalika SomeKrishanu MukherjeeSomenath Sit
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Objective• Web Crawling from IMDB for 3 sequels of The Hobbit.
• Creation of Term Document Matrix and WordCloud
• Dimension Reduction using Latent Semantic Analysis
• Influencing Words in Ratings
• Comparison of sentiments expressed in reviews and ratings given
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Web Crawling
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Cleaning of TDM
TDM Dictionary
Final TDM
Filtered TDM
Excluded few common but unnecessary words like "hobbit", "film", "movie", "movies“ etc.
Dictionary with common english words
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Dominating Words in TDM
Hobbit - 2012 Hobbit - 2013 Hobbit - 2014
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Dimension Reduction using LSA
TK DK SK
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Important Variables in TK matrix
Built a model with “satisfaction” as response variable, to find out which variable are having more power in predicting the “Ratings
satisfaction=ifelse(Ratings<5,"Dissatisfied",ifelse(Ratings<7,"Satisfied","Impressed!"))
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Dimension Reduction using LSA
• Plotted variable importance with Scree Plot.
• Take optimal no of variables (documents) to filter DK matrix.
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DK matrix with important variables
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For Hobbit-2012
• Story ,book, like these words are having deciding power in “Ratings”.
• People talked more about the book and the story line.
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For Hobbit-2013
• Series ,good , great, story these words are having deciding power in “Ratings”.
• In 2013 also viewers were only impressed with the story, battles etc.
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For Hobbit-2014
• Beside like, good; bad, story these words are also having deciding power in “Ratings”.
• Along with the good words, some negative words have been used here.
• Story, book these things are not that effecting in comparison with previous sequels.
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Sentiment Analysis• A basic task in sentiment analysis is classifying
the polarity of a given text at the document, sentence, or feature/aspect level — whether the expressed opinion in a document, a sentence is positive, negative, or neutral.
• We performed sentiment analysis (polarity) on the movie reviews of Hobbit and its sequels .
• We used R for the analysis.
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Average Ratings
Hobbit :An Unexpected Journey (2012)
For Hobbit: The Desolation of Smaug (2013)
For Hobbit: The Battle of the Five Armies (2014)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
3.65
2.52
4.13
Key Findings………
• For Hobbit :An Unexpected Journey (2012), 97% of the negative ratings had a negative polarity for the corresponding reviews, while 78% of the positive ratings had a positive polarity for the corresponding reviews.
• 76.5% of the ratings were negative.• The average polarity of the reviews was
(0.012).
Key Findings….(contd)…
• For Hobbit: The Desolation of Smaug (2013), 85% of the negative ratings had a negative polarity for the corresponding reviews, while 60% of the positive ratings had a positive polarity for the corresponding reviews.
• 89% of the ratings were negative.• The average polarity of the reviews was
(0.004).
Key Findings….(contd)…
• For Hobbit: The Battle of the Five Armies (2014), only 3% of the negative ratings had a negative polarity for the corresponding reviews, while 100% of the positive ratings had a positive polarity for the corresponding reviews.
• 68% of the ratings were negative.• The average polarity of the reviews was (0.005).
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Polarity Comparison - Region wise
Hobbit 2012 Hobbit 2013
Hobbit 2014
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Polarity Comparison – Region wise
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