Introduction In today’s digital age, social media platforms like Twitter have become crucial for staying updated on the latest trends and news. Analyzing Twitter data can provide valuable insights into what’s happening around the world in real time. In this blog post, we’ll explore the latest 10 tweets using R and dive into the significance of this data. Fetching Twitter Data Using R To begin with, we fetched the latest 10 tweets using the R programming language. Here’s the code snippet we used: library(dplyr) library(readr) dataset <- read_csv(“D:/archive (1)/Tweets.csv”) dataset <- dataset %>% mutate(tweet_created = as.POSIXct(tweet_created, format = “%d-%m-%y %H:%M”)) latest_10_tweets <- dataset %>% arrange(desc(tweet_created)) %>% select(tweet_id, name, text) %>% head(10) print(latest_10_tweets) Analyzing the tweets Tweet_id User_name Texts 5.70306 Cairdin What @dhepburn said. 5.70307 Jnardino plus you’ve added commercials to the experience… tacky. 5.7030...