newsflash (version 0.6.0)

top_trending: Top Trending Tables

Description

You likely want to use top_trending_range() instead of this as it has a much friendlier user API. Use this if you want granular control over which times you are looking for and are willing to do the to/from GMT conversion on your own.

Usage

top_trending(ymd = Sys.Date(), hour = 0:23, minute = c(0, 15, 30, 45))

Arguments

ymd

a Date object or a character string in YYYYMMDD or YYYY-MM-DD format. (Defaults to today).

hour

0 to 23 (Defaults to 0)

minute

one of 0, 15, 30, or 45. (Defaults to 0)

Value

list with

  • DateGenerated (character vector)

  • OverallTrendigTopics (character vector)

  • StationTrendingTopics (data frame with a Station column and a list column of Topics)

  • StationTopTopics (same structure as StationTrendingTopics)

  • OverallTrendingPhrases

Details

GDELT now generates a snapshot every 15 minutes that records all of the "top trending" tables into a single archive enabling users to ook back over time at what was trending in 15 minute increments historically back to midnight on 2017-09-07.

Note that the archives are generated every 15 minutes based on the television shows that have completed processing at that time. It can take several hours for a show to be fully processed by the Internet Archive and available for processing, thus the presence/absence of a topic in these files should not be used to date it precisely to that 15 minute mark, but rather as a rough temporal indicator of what topics were trending up/down in that general time frame. For precise timelines, you should take a topic from this archive and run a search on it using the main Television Explorer interface, select a timeframe of 72 hours and use the resulting timeline to precisely date the topic's coverage (since the Explorer timeline is based on the broadcast timestamp of the show, even if it is processed hours later).

The time is expected to be GMT for the API.

Examples

Run this code
# NOT RUN {
top_trending(hour=14, minute=30)
# }

Run the code above in your browser using DataLab