Small errors have been updated and everything works fine besides the correlation function

library(lubridate)

#loading necessary dataset

load("D:/Hohenheim/SEM 3/ADS/introads_ass2_team18/01_data/raw/gamereviews.RData")

load("D:/Hohenheim/SEM 3/ADS/introads_ass2_team18/01_data/raw/rev.summary.RData")

load("D:/Hohenheim/SEM 3/ADS/introads_ass2_team18/01_data/reviews.clean.RData")

load("C:/Users/akluj/SEM_3/ADS/introads_ass2_team18/01_data/raw/gamereviews.RData")

load("C:/Users/akluj/SEM_3/ADS/introads_ass2_team18/01_data/raw/rev.summary.RData")

load("C:/Users/akluj/SEM_3/ADS/introads_ass2_team18/01_data/reviews.clean.RData")

# Only keeping necessary columns for analysis

# Manual sentiment analysis-----------------------------------------------------

# Loading of necessary words lists taken from Kaggel by Hu and Bing Liu

setwd("D:/Hohenheim/SEM 3/ADS/introads_ass2_team18/00_docs")

setwd("C:/Users/akluj/SEM_3/ADS/introads_ass2_team18/00_docs")

positive.words <- readLines("positive-words.txt")

negative.words <- readLines("negative-words.txt")

# A review score based from revsummary file, it was dowanloaded in the 1st assisgnement

overall.review.score <- revsummary$review_score

print(overall.review.score)

# Calculating correlation betwwen an average sentiment score and overall review score

correlation <- cor(avg.sent.score, overall.review.score)

# Calculating correlation between an average sentiment score and overall review score

# correlation <- cor(avg.sent.score, overall.review.score)

# Printing the correlation coefficient

print(paste("Correlation between average sentiment and overall score:", correlation))

# print(paste("Correlation between average sentiment and overall score:", correlation))

# Q4 Sentiment variation -------------------------------------------------------

ggsave(file= "C:/Users/hetvi/OneDrive/Desktop/Sentiment variation.jpg", 

       width=15, height=15, units = "cm", dpi=1600)

# checking on highest sentiment date

high.index <- which.ma

# Finding the index of the review with the highest helpful votes

high.index <- which.max(total.score.date$total_sentiment)

# Getting the corresponding review 

# Getting the corresponding date

high.count <- total.score.date[high.index,]

print(high.count)

# Printing a result

cat("A highest sentiment score", high.count$total_sentiment, "was recorded on", format(high.count$date, "%Y-%m-%d"))

cat("A highest sentiment score of", high.count$total_sentiment, "was recorded on", format(high.count$date, "%Y-%m-%d"))