Get Twitter trends data.

get_trends(woeid = 1, lat = NULL, lng = NULL, exclude_hashtags = FALSE,
  token = NULL, parse = TRUE)

Arguments

woeid

Numeric, WOEID (Yahoo! Where On Earth ID) or character string of desired town or country. Users may also supply latitude and longitude coordinates to fetch the closest available trends data given the provided location. Latitude/longitude coordinates should be provided as WOEID value consisting of 2 numeric values or via one latitude value and one longitude value (to the appropriately named parameters). To browse all available trend places, see trends_available

lat

Optional alternative to WOEID. Numeric, latitude in degrees. If two coordinates are provided for WOEID, this function will coerce the first value to latitude.

lng

Optional alternative to WOEID. Numeric, longitude in degrees. If two coordinates are provided for WOEID, this function will coerce the second value to longitude.

exclude_hashtags

Logical, indicating whether or not to exclude hashtags. Defaults to FALSE--meaning, hashtags are included in returned trends.

token

Every user should have their own Oauth (Twitter API) token. By default token = NULL this function looks for the path to a saved Twitter token via environment variables (which is what `create_token()` sets up by default during initial token creation). For instruction on how to create a Twitter token see the tokens vignette, i.e., `vignettes("auth", "rtweet")` or see ?tokens.

parse

Logical, indicating whether or not to parse return trends data. Defaults to true.

Value

Tibble data frame of trends data for a given geographical area.

See also

Other trends: trends_available

Examples

# NOT RUN { ## Retrieve available trends trends <- trends_available() trends ## Store WOEID for Worldwide trends worldwide <- trends$woeid[grep("world", trends$name, ignore.case = TRUE)[1]] ## Retrieve worldwide trends datadata ww_trends <- get_trends(worldwide) ## Preview trends data ww_trends ## Retrieve trends data using latitude, longitude near New York City nyc_trends <- get_trends_closest(lat = 40.7, lng = -74.0) ## should be same result if lat/long supplied as first argument nyc_trends <- get_trends_closest(c(40.7, -74.0)) ## Preview trends data nyc_trends ## Provide a city or location name using a regular expression string to ## have the function internals do the WOEID lookup/matching for you (luk <- get_trends("london")) # }