12/16/2023 0 Comments Download https tweetdeck twitter com![]() # 6 Humanity strikes back at Join the #WorldToTrump open letter thats sweeping the planet! #Trump # 5 RT Trump: No Salary for Me as President #maga #trump # 4 A madman has been given the keys to the surveillance state | Electing #Trump is a major #FAIL for #America ![]() # 3 RT Instead of telling us that not all #Trump voters are racist, how about condemning the acts of racism being committed in his na # 2 Also relevant, my follow-up tweet from last June #Hillary #Trump #notmypresident #safetypin\n ![]() # 1 RT #Trump less than 48 hrs:\n\nRespects Obama\nNot Repealing OC\nWants Bill Clinton as Advisor\nNo Wall\nNo Deportation\n#ChrisChri # 10 disgust 191 pos_tw_ids % filter(sentiment = "positive") %>% distinct(id)įd_df %>% inner_join(pos_tw_ids, by = "id") %>% select(text) %>% slice(1:10) # text ![]() # 6 abandoned fear Fd_words_sentiments % inner_join(nrc, by = "word")įd_words_sentiments %>% group_by(sentiment) %>% summarise(n = n()) %>% arrange(desc(n)) # A tibble: 10 × 2 with 11 more rows nrc % filter(lexicon = "nrc") %>% select(word, sentiment) Unnest_tokens(word, text, token = "regex", pattern = reg) %>%įd_words %>% group_by(word) %>% summarize(n = n()) %>% arrange(desc(n)) %>% top_n(20) # Selecting by n # A tibble: 21 × 2 # 10 Put your button on any page! 5 0.005 Fd_df %>% group_by(screenName) %>% summarise(n = n()) %>% mutate(percent_of_tweets_Fd = n/ sum(n)) %>% arrange(desc(n)) %>% top_n(10) # Selecting by percent_of_tweets_Fd # A tibble: 48 × 3 Mutate(percent_of_tweets = n / sum(n)) %>%įd_platform %>% top_n(10) # Selecting by percent_of_tweets # A tibble: 10 × 3 with 1 more variables: n #extract the platformįd_df$statusSource = substr(Fd_df$statusSource, ![]() # 9 Put your button on any page! Hootsuite Generosity num_tweets % group_by(statusSource) %>% summarise(n = n()) %>% arrange(desc(n)) %>% top_n(10) # Selecting by n # A tibble: 10 × 2 ![]()
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