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Updated ModiTwitterSentimentAnalysis.R #1

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Updated ModiTwitterSentimentAnalysis.R #1

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12 changes: 6 additions & 6 deletions ModiTwitterSentimentAnalysis.R
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Original file line number Diff line number Diff line change
@@ -1,17 +1,16 @@

#Installing the packages
install.packages("SnowballC")
install.packages("twitteR")
install.packages("syuzhet")

#Packages Required
#Running the packages

library("SnowballC")
library("twitteR")
library("syuzhet")

#For the Keys You need a Twitter Developer Account. Apply at https://apps.twitter.com/ to get the keys.
#For the Keys You need a Twitter Developer Account. Apply at https://apps.twitter.com/ to get the keys. It will take 3-7 days for the mail to arrive


consumer_key <- 'xxxxwIVGxxxxGF86n2Pxxxx'
consumer_secret <- 'xxxxh1q18eKlVJT2ECWnxxxxsqY0O2SfjYfy1UEX28Eyz5xxxx'
access_token <- 'xxxx374159-VFnclbH1D2xxxxxklk1hA0eRErFGJ1gwvrkxxxx'
Expand Down Expand Up @@ -53,12 +52,10 @@ head(emotion.df2)

head(emotion.df2)


sent.value <- get_sentiment(word.df)

most.positive <- word.df[sent.value == max(sent.value)]

most.positive
sent.value <- get_sentiment(word.df)

most.positive <- word.df[sent.value == max(sent.value)]
Expand All @@ -72,11 +69,14 @@ most.negative

sent.value

#positive tweets
positive.tweets <- word.df[sent.value > 0]
head(positive.tweets)

#negative tweets
negative.tweets <- word.df[sent.value < 0]
head(negative.tweets)

#neutral tweets
neutral.tweets <- word.df[sent.value == 0]
head(neutral.tweets)