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Data files for the paper "Forecasting the pulse: How deviations from regular patterns in online data can identify offline phenomena"
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README.md
tag-volume.csv
total-volume.csv

README.md

twitter-diversity

Data files for the paper "Forecasting the pulse: How deviations from regular patterns in online data can identify offline phenomena"

There are two comma-separated files:

  • tag-volume.csv contains 1000 data series consisting of the tweet volume of the 1000 most popular hashtags
  • total-volume.csv contains a single data series of the total volume of tweets per hour

Both files include a date field that follows the ISO standard, ie: YYYYMMDDHH (year, month, day, hour).

These files can be easily imported into a statistics package such as R:

tags <- read.csv("tag-volume.csv", header=TRUE)
tags$date <- as.POSIXct(strptime(tags$date, format='%Y%m%d%H'))

Questions and suggestions can be submitted via pull request or directed at the authors:

pascal.juergens@googlemail.com and
andreas.jungherr@googlemail.com

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