rtweet (version 0.6.0)

get_trends: Get Twitter trends data.

Description

Get Twitter trends data.

Usage

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

OAuth token. By default token = NULL fetches a non-exhausted token from an environment variable. Find instructions on how to create tokens and setup an environment variable in the tokens vignette (in r, send ?tokens to console).

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 {
# }
# 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"))

# }
# NOT RUN {
# }

Run the code above in your browser using DataCamp Workspace