sentiment_dist_plot: Sentiment Distribution Plot

In Ritayu09/Test_R_Package: Generates Text Sentiment Score Using Microsoft API

Description

The function produces a density or boxplot for the sentiment score generated using the Microsoft sentiment analysis API. Function divides data into negative, neutral and positive sentiment based on user input values and produces distribution plot for each of the sentiment class.

Usage

sentiment_dist_plot(data, negative_cutoff = 0.35, positive_start = 0.65, graph_alpha = 0.5, graph_type = 'density')

Arguments

data	Dataframe containing 'Sentiment Score' column for plotting distribution plot.
negative_cutoff	Maximum cutoff value for sentiment score to be considered as 'Negative'. The cutoff value will not be bounded (i.e. not inclusive) for negative sentiment. Scores from 0 to cutoff will be considered negative sentiment.
positive_start	Minimum value for sentiment to be considered as 'Positive'. The value is inclusive for positive sentiment tagging. Scores between positive_start to 1 will be considered positive sentiment.
graph_alpha	alpha parameter controls the transparency of the plot. Default value considered is 0.5 and it varies from 0 (transparent) to 1 (opaque).
graph_type	Parameter for type of plot. Function accepts 'density' and 'boxplot' as input values and default value is 'density'.

Details

The function helps visualize the results generated for sentiment analysis. The 'Sentiment Score' generated for each sentence is classified under 'Negative', 'Neutral' and 'Positive' sentiment considering user input and density or boxplot is generated for each of the sentiment class to further understand the score distribution within the class. Sentiment score between 'negative_cutoff' and 'positive_start' are tagged under 'Neutral' category.

Value

Function returns requested graph using ggplot2 library.

Examples

require(ggplot2)

# using get_batch_sentiment function available in the same package to generate sentiment score

# sentiment_data <- get_batch_sentiment (dataset, "eda0526b71ff44b29c", "westcentralus")

# density plot

# sentiment_dist_plot(sentiment_data, negative_cutoff = 0.35, positive_start = 0.65, graph_alpha = 0.5, graph_type = 'density')

# boxplot

# sentiment_dist_plot(sentiment_data, negative_cutoff = 0.3, positive_start = 0.6, graph_alpha = 0.75, graph_type = 'boxplot')

Ritayu09/Test_R_Package documentation built on June 6, 2020, 2:29 a.m.