Twitter Hashtag #appleindia Text Mining using R

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Social Media and Sentiment Analysis of Tweets about Apple India Hashtag #appleindia By Nikhil Gadkar +91 8882135642 [email protected] 1

Transcript of Twitter Hashtag #appleindia Text Mining using R

Page 1: Twitter Hashtag #appleindia Text Mining using R

Social Media and Sentiment Analysis of Tweets about Apple India

Hashtag #appleindiaBy

Nikhil Gadkar+91 8882135642

[email protected]

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Index

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Introduction and Inference Slide3

Common Words in Tweets Slide4

Word Cloud Slide5

Word Cluster Slide6

Word Correlation Slide7

Network of Frequent Terms Slide8

Cohesive Blocks of Frequent Terms Slide9

Sentiment Index Slide10

Appendix – Tweets raw data Slide12

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IntroductionData : 799 tweets from the twitter that contain the keywords Apple and India. The date range is 6 April 2016 to 16 April 2016. (All I could download)

Objective : To understand what Apple Users in India are talking about and what is the sentiment.

Inference : The sentiment is largely neutral.(Please note I have removed the word “Apple” and “India” in my analysis because it would distort the analysis)The main topic of discussion is iPhone and its corporate lease plan. I was not aware that there is a corporate lease plan, in spite of the fact thatthe company I work for, IBM, has a partnership with Apple. 2 years, with IBM, never seen a single email on any plan.

Are there any corporate lease plans for the PC’s and laptops?

The most interesting slide is No:7, which shows the words with maximum correlation with iPhone.

Please view the subsequent slides for more details.

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Common Words in Tweets

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Word Cloud

The size of the word is proportional to its frequency

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Word Cluster

This is just a grouping of terms that appear together

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Word Correlation

Please note, some terms are incomplete and it is difficult to guess those. (Punjabkesari, the news paper has tweeted frequently)

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Network of Frequent Terms

This shows how the frequent terms are connected. Here, also, size of the word is proportional to its frequency

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Cohesive Blocks of Frequent Terms

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Sentiment Index

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Appendix

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AppleIndiaForum Tweets

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Microsoft Excel Comma Separated Values Fi