WeatherSentiment (version 1.0)

corr_analys: Calculate Correlation between Sentiment and Weather Variable

Description

This function calculates the Pearson correlation coefficient between sentiment scores extracted from tweets and a weather variable (e.g., temperature) in a merged dataset.

Usage

corr_analys(t, w, com_var = "Date", var1 = "T1", var2 = "T2")

Value

The Pearson correlation coefficient between sentiment scores and the weather variable.

Arguments

t

A data.frame containing tweets with a 'text' column

w

A data.frame containing weather data with a column matching the 'com_var'

com_var

The name of the common variable for merging the tweet and weather data. Defaults to "Date".

var1

The name of the column in 't' containing the tweet text. Defaults to "T1".

var2

The name of the column in 'w' containing the weather variable. Defaults to "T2".

Author

Leila Marvian Mashhad and Andriette Bekker and Mohammad Arashi and Priyanka Nagar.

Examples

Date1 <- c('2024-01-01', '2024-01-02')
T1 <- c('I love sunny days', 'Rainy days are the worst') 
tweet <- data.frame(Date = Date1 , T1 = T1)
weather <- data.frame(Date = Date1, T2 = c(25, 15))
cor1 <- corr_analys(tweet, weather, com_var = "Date", var1 = "T1", var2 = "T2")
print(cor1)