text analytics

TEXT ANALYTICS

Analysis of reviews fetched from FLIPKART.COM for

MOTO-G (2nd gen)

3/19/2015 Roma Agrawal (A14026) 1

Objective

• Web Crawling from www.filpkart.com for Mobile “MOTO G (2nd gen)”

• Creation of Term Document Matrix and WordCloud

• Dimension Reduction using Latent Semantic Analysis

• Clustering on the basis of both Terms and Documents

• Analysis of ratings given

• Comparison of sentiments expressed in reviews and ratings given

3/19/2015 Roma Agrawal (A14026) 2

Web Crawling

3/19/2015 Roma Agrawal (A14026) 3

Creation of TDM and WordCloud

3/19/2015 Roma Agrawal (A14026) 4

Dimension Reduction using LSA

3/19/2015 Roma Agrawal (A14026) 5TK DK SK

Plotting Terms wrt V1 and V2

3/19/2015 Roma Agrawal (A14026) 6

3/19/2015 Roma Agrawal (A14026) 7

Plotting Terms wrt V1 and V3

3/19/2015 Roma Agrawal (A14026) 8

Plotting Terms wrt V2 and V3

3/19/2015 Roma Agrawal (A14026) 9

Plotting Doc wrt V1 and V2

3/19/2015 Roma Agrawal (A14026) 10

Plotting Doc wrt V1 and V3

3/19/2015 Roma Agrawal (A14026) 11

Plotting Doc wrt V2 and V3

Clustering (for Terms)

3/19/2015 Roma Agrawal (A14026) 12

3/19/2015 Roma Agrawal (A14026) 13

WordCloud for each Clusters

3/19/2015 Roma Agrawal (A14026) 14

Clustering (for Doc)

Analysis of ratings given

3/19/2015 Roma Agrawal (A14026) 15

No Rating was missing

What review text is saying!

3/19/2015 Roma Agrawal (A14026) 16

Some agreement Between “what review text is saying” and “what rating given” is shown by this count

Not able to create polarity for 6 reviews, replaced by group average polarity

3/19/2015 Roma Agrawal (A14026) 17

Classification on “satisfaction”

Top 6 imp words which have negative meaning

Top 6 imp words which have positive meaning

3/19/2015 Roma Agrawal (A14026) 18