knitr::opts_chunk$set(echo = TRUE)
#Loading this will enable you to work with æøå - VERY IMPORTANT Sys.setlocale(category = "LC_ALL", locale = "UTF-8") #load packages and data library(pacman) p_load(ggplot2,stringr,dplyr,tidyverse, remotes) #add your favorite packages fv_all <- read_csv("fv_all.csv") #look at the data, check if classes make sense, e.g. $text should be character head(fv_all$text, 10) colnames() class() #Load sentida and apply it to one of the tweets, try both total and mean remotes::install_github("Guscode/Sentida", force = T) library(Sentida) ?sentida #select a leader from one of the Danish political parties (https://www.dr.dk/nyheder/politik/resultater/folketingsvalg). From fv_all make a new dataframe including only tweets mentioning this person. #E.g.: paludan <- filter(fv_all, str_detect(fvhash$text, "Paludan") == T) ### You might want to do some preprocessing of the text here. str_remove_all() is cute, tolower() is cool, str_replace_all() is sexy. Make the tweets lowercase and remove all numbers (Major hint alert: str_remove_all(paludan$text,[:digit:])) #Make a new row in the dataframe with sentiment score of every tweet mentioning this person (e.g use lapply() or make a loop if you dare) ?lapply
#what is his/her mean sentiment score? ###Bonus: What is their mean sentiment score per day? !WARNING ADVANCED PLEASE SKIP! lifesaver: aggregate() #Compare your political leader to one from another party #Did the parties who won less mandates than the last election have a worse sentiment score than the rest? #Are there any correlations between sentiment score and amount of favourites/retweets?
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