Setting up a script

Set up your account code & filter

Once you’ve set up an account code and filter, you can use this in your various metrics:

# First you'll want to set an account code
code <- "QUIR01BA" 

# Then set a filter - remember to add a brand
filter <- "published inthelast week and relevancy is relevant and brand isorchildof 10006"

If you want to find brand IDs from an account, look at the article on finding brands using R.

Getting volume and sentiment

# To use a function from chartingtest, you'll first need to load the library
library(chartingtest)

# Now you can get a breakdown of volume and sentiment (including net sentiment) by date
volume_sentiment_metric(code, filter)

published	count	netSentiment	netSentimentPercent	uniqueAuthors	positiveSentiment	positivePercent	negativePercent	neutralSentiment	neutralPercent
2018-08-30	0	0	0.00	0	0	0.0%	0%	0	0%
2018-08-31	4	3	0.75	3	3	75.0%	0%	1	25%
2018-09-01	5	0	0.00	2	0	0.0%	0%	5	100%
2018-09-02	1	0	0.00	1	0	0.0%	0%	1	100%
2018-09-03	0	0	0.00	0	0	0.0%	0%	0	0%
2018-09-04	1	0	0.00	1	0	0.0%	0%	1	100%
2018-09-05	3	1	0.33	2	1	33.3%	0%	2	67%
2018-09-06	0	0	0.00	0	0	0.0%	0%	0	0%

Grouping by day, week or month

# You can group by day, week or month
volume_sentiment_metric(code, filter, group = "week")

published	count	netSentiment	netSentimentPercent	uniqueAuthors	positiveSentiment	positivePercent	negativePercent	neutralSentiment	neutralPercent
2018-08-30	0	0	0.00	0	0	0.0%	0%	0	0%
2018-08-31	4	3	0.75	3	3	75.0%	0%	1	25%
2018-09-01	5	0	0.00	2	0	0.0%	0%	5	100%
2018-09-02	1	0	0.00	1	0	0.0%	0%	1	100%
2018-09-03	0	0	0.00	0	0	0.0%	0%	0	0%
2018-09-04	1	0	0.00	1	0	0.0%	0%	1	100%
2018-09-05	3	1	0.33	2	1	33.3%	0%	2	67%
2018-09-06	0	0	0.00	0	0	0.0%	0%	0	0%

Saving to CSV

# To save to CSV, set save=TRUE - you'll be asked to enter a filename
volume_sentiment_metric(code, filter, group = "day", save=TRUE)

# If you want to run the code as part of a script, you can specify the file upfront and it will save automatically
volume_sentiment_metric(code, filter, group = "day", file="C:/Users/brandseye/Documents/volume_sentiment.csv")

More examples

Sentiment metric

# Get data for the sentiment metric
sentiment_metric(code, filter)

Sentiment	Count	Percentage
Negative	0	0.0%
Neutral	5	71.4%
Positive	2	28.6%

Stats metric

# Get data for the stats metric
stats_metric(code, filter)

Metric	Value
Volume	14
Authors	6
OTS	18784
Engagement	2
Sites	3
Verified Sample	7
Positive	2
Neutral	5
Negative	0
Positive %	28.6%
Neutral %	71.4%
Negative %	0%

Putting it all together

Here is an example of a script you might run to get all the CSVs for a particular report. In this example we will set the filter only once, but you could use multiple filters if you like, or add additional filtering to a particular metric.

How to run the example:

Copy this code into a new file (File -> New File -> R Script)
Replace PATH_TO_YOUR_FOLDER with the folder where you’d like to save the CSVs, e.g. C:/Users/You/YourReport
Give it a try by hitting Run

library(chartingtest)

# Loading 'glue' so we can set the folder name once and then stick it together with the filename
library(glue)

# Set account code to use
code <- "QUIR01BA" 

# Set the filter to use
filter <- "published inthelast week and relevancy is relevant and brand isorchildof 10006"

folder <- "PATH_TO_YOUR_FOLDER"

# Get the volume breakdown
volume_sentiment_metric(code, 
                        filter, 
                        file = glue(folder, "/volume-metric.csv")) # join the folder name onto the file name

# Get the hourly breakdown
time_of_day_metric(code, 
                   filter, 
                   file = glue(folder, "/time-of-day.csv"))

# Top 10 authors
authors_metric(code, 
               filter, 
               truncateAt = 10, #Only give me the first 10 authors
               glue(folder, "/authors-metric.csv"))

# Top 10 sites
sites_metric(code, 
             filter, 
             truncateAt = 10, #Only give me the first 10 sites
             file = glue(folder, "/sites-metric.csv"))

# Sentiment breakdown
sentiment_metric(code, 
                 filter, 
                 file = glue(folder, "/sentiment-metric.csv"))

# Top 10 words
wordcloud_metric(code, 
                 filter, 
                 file = glue(folder, "/wordcloud-metric.csv"))

Lara Basson

2018-09-06