Classify users/accounts in Twitter data as bots or not bots.
Returns a numeric vector of probabilities
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Object to be classified. Can be user IDs, screen names, or data frames returned by rtweet.
Logical indicating whether to use the fast (lighter) model. The default (fast = FALSE) method uses the most recent 100 tweets posted by users to determine the probability of bot. The fast (fast = TRUE) method only uses users-level data, which is easier to get in large quantities from Twitter's APIS but overall less accurate.
Classifications for all users expressed as probability of whether each account is a bot.
A named (screen names or user IDs depending on input) numeric vector of probabilities
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## Not run: ## vector of screen names sns <- c("kearneymw", "geoffjentry", "p_barbera", "tidyversetweets", "rstatsbot1234", "RStatsStExBot") ## get and view bot probability estimates twb <- tweetbotornot(sns) twb ## ask for the fast (user-level data only) version twbf <- tweetbotornot(sns, fast = TRUE) twbf ## End(Not run)
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