citation-sentiment-analysis
https://github.com/shubhangichaturvedi02/citation-sentiment-analysis
Science Score: 18.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (7.6%) to scientific vocabulary
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README.md
Citation-Sentiment-Analysis
The R code of implementation is provided. In reserach papers, it is very common to see papers being cited in other papers for reference purposes - some of which are appreciated for their work, some to propose an advancement of the cited work and some others just refer to the cited paper for their information -all giving their opinions about the mentioned paper. We aims to measure such opinions as the sentiment polarity which the citation context carries towards the cited content.
The objective is to extract citations - both implicit and explicit in a research paper, calculate its sentiment polarity using various R tools in RStudio. The sentiment polarity score will tell us how positive, negative or neutral the citation is by its closeness to 0 and otherwise.
Analysis of citation sentiment would open up many exciting new applications in bibliographic search and in bibliometrics, i.e., the automatic evaluation the influence and impact of individuals and journals via citations. A very useful application of sentiment analysis is in ranking sites, papers by calculating authors impact through polarity of the citation.
Tried to extract maximum citations but the style of citation we extract are restricted to APA (American Psychological Association) Style which includes three important information about the referenced work, author's last name, work's date of publication and page number(where the direct quote is written).
For Ui- Shiny tool of R is utilised. Video of UI is uploaded.
Owner
- Name: Shubhangi Chaturvedi
- Login: shubhangichaturvedi02
- Kind: user
- Location: India
- Repositories: 1
- Profile: https://github.com/shubhangichaturvedi02
Software Developer | Python | Django | Flask | Javascript | MySQL | Machine Learning | Data Analysis
Citation (citation_Sentiment_analysis_code/app.R)
ui <- fluidPage(
#adding radio button
radioButtons("radio", label = h4("CHOOSE PAPER NAME"),
choices = list("The Anselm Corpus: Methods and Perspectives" = 1, "Improving historical spelling normalization with bi-directional LSTMs
and multi-task learning" = 2),
selected = 1),
hr(),
#adding button
actionButton("btn", h4("FIND CITATIONS SENTIMENT")),
#browsing text file
fileInput("file", h4("Select the text file from folder")),
#output field
verbatimTextOutput("value"),
verbatimTextOutput("text"),
verbatimTextOutput("text1"),
sidebarLayout(
numericInput("state", h4("Choose a author serial number:"),c(0,1,2)),
verbatimTextOutput("text3")
)
)
server <- function(input, output, session) {
#adding function file
source("fun.R")
#calculate function when button is clicked
observeEvent(input$btn, {
#new.function(6)
output$text<-renderText(onerun<-Citation_sentiment_analysis(as.integer(input$radio)))
})
#displaying of output file
output$text1<- renderText({
filePath <- input$file$datapath
fileText <- paste(readLines(filePath), collapse = "\n")
fileText
})
output$text3 <- renderText({fun1(input$state)})
}
# Run the application
shinyApp(ui = ui, server = server)