#
# This is the server logic of a Shiny web application. You can run the
# application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
.libPaths(c("/usr/local/lib/R/site-library", .libPaths()))
library(shiny)
# Define server logic required to draw a histogram
shinyServer(function(input, output,session) {
#create_readData_file<-"/srv/shiny-server/myapp/readData.txt"
create_readData_file<-"./readData.txt"
#xgbalgorithm_file_path<-"/srv/shiny-server/myapp/xgboost.R"
#nbalgorithm_file_path<-"/srv/shiny-server/myapp/nbase.R"
#svgalgorithm_file_path<-"/srv/shiny-server/myapp/sv.R"
xgbalgorithm_file_path<-"./xgboost.r"
nbalgorithm_file_path<-"./nbase.r"
svgalgorithm_file_path<-"./sv.r"
#xgbcreate_Result_file<- "/srv/shiny-server/myapp/result-xgboost.txt"
#nbcreate_Result_file<- "/srv/shiny-server/myapp/result-nbase.txt"
#svcreate_Result_file<- "/srv/shiny-server/myapp/result-sv.txt"
xgbcreate_Result_file<- "./result-xgboost.txt"
nbcreate_Result_file<- "./result-nbase.txt"
svcreate_Result_file<- "./result-sv.txt"
#on submit button condition
observeEvent(input$submit, {
# Esta variable al defini con el fin porque estoy quitando «input$nbase» fron the ui.R
# Luego sustitui «input$nbase» por «variable_nbase» en todo el codigo
# Fue la forma mas facil que encontre para quitar «input$nbase»
# Si quiero colocar input$nbase lo que tengo que hacer es sustituir «variable_nbase» por «input$nbase» y comentar esta variable
variable_nbase = FALSE
# if input text and no file upload and none of the algorithms selected
if((!(input$xgboost) && !(variable_nbase) && !(input$svm)) && (input$text =="" && is.null(input$file1)) )
{
showModal(modalDialog(
title = "Error",
"You have to enter the text of a news article into the corresponding input field",
easyClose = TRUE
))
}
# elseif only no of the algorithms selected
else if((!(input$xgboost) && !(variable_nbase) && !(input$svm)))
{
showModal(modalDialog(
title = "Error",
"Please! select at least one algorithm",
easyClose = TRUE
))
}
# elseif only input text and no file upload
else if((input$text =="" && is.null(input$file1)))
{
showModal(modalDialog(
title = "Error",
"Either File is not uploaded or text field is empty",
easyClose = TRUE
))
}
# check if text input is filled
else if(input$text!="" ){
#save input-text into readData.txt
sink(create_readData_file)
cat(input$text)
sink()
text<-readtext(create_readData_file)
texto<-paste('
Input Text
',text,'
')
warning<-paste('
Important
The results shown above were calculated from a Supervised Machine Learning Model built from a dataset of 60,000 news articles.
The best accuracy was obtained with the Gradient Boosting (XGBoost) algorithm. We got 78% accuracy. Therefore, keep in mind that the most reliable result is the one returned by that algorithm.
It is very important to notice that a complete News Article must be entered so the models are able to work correctly. You cannot input only a sentence and expect our models to validate if that sentence is true or fake.
Also notice that the definition of Fake News used in this project is:
Deliberately distorted information that secretly leaked into the communication process in order to deceive and manipulate (Vladmir Bitman). Therefore, our Machine Learning Models are only able to detect this kind of Fake News.
You can test the app using some news articles from a very unreliable source, such as: https://thepeoplesvoice.tv
')
if(input$xgboost && variable_nbase && input$svm){
print ("xgboost and Naive Bayes and Support Vector Machine")
#xgboost
source(xgbalgorithm_file_path)
#after script is run it saves result into result
result_File<- xgbcreate_Result_file
resultant_xgb<-readtext(result_File)
#nbayes
source(nbalgorithm_file_path)
result_File<- nbcreate_Result_file
resultant_nb<-readtext(result_File)
#svm
source(svgalgorithm_file_path)
result_File<- svcreate_Result_file
resultant_svm<-readtext(result_File)
text<-readtext(create_readData_file)
if (resultant_xgb$text==0)
{
res_xgb="Reliable"
color_xgb<-"The news article is RELIABLE"
}
else if(resultant_xgb$text==1)
{
res_xgb="Fake"
color_xgb<-"The news article is FAKE"
}
if (resultant_nb$text==0)
{
res_nb="Reliable"
#color_nb<-"
", sep = ' '))
})
}
else if(input$xgboost && !(variable_nbase) && !(input$svm)){
print ("xgboost")
#xgboost
source(xgbalgorithm_file_path)
#after script is run it saves result into result
result_File<- xgbcreate_Result_file
resultant_xgb<-readtext(result_File)
text<-readtext(create_readData_file)
if (resultant_xgb$text==0)
{
res_xgb="
TRUE
"
color_xgb<-"The news article is RELIABLE"
}
else if(resultant_xgb$text==1)
{
res_xgb="Fake"
color_xgb<-"The news article is FAKE"
}
#this section is for shwing data from result.txt
output$content <- renderUI({
if (res_xgb == "Reliable"){
color_font_xgb = "blue"
} else {
color_font_xgb = "red"
}
str1<-paste("