Build a Sentiment Timeseries Forecasting Pipeline
Time series forecasting algorithms are a common method for predicting future values based on historical data using sequential data, such as snowfall per hour, customer sign-ups per day, or quarterly sales data.
In this R recipe, we’ll show how to easily link algorithms together to create a data analysis pipeline for sentiment time series forecasting.
For the full blog post related to this recipe, see Forecasting Sentiment Analyis with R.
install.packages("Algorithmia") install.packages("stats") library(algorithmia) library(stats)
You’ll also need a free Algorithmia account, which includes 5,000 free credits a month.
Find this line in the script:
client <- getAlgorithmiaClient("YOUR_API_KEY")
and add in your API key.
How to Analyze Timeseries Sentiment
After putting in your own API key to the line above run it in your console environment: