Fake news is loosely defined as “lies and propaganda that are falsely presented as news, such as cruel headlines or deliberately manipulated photos and videos, for hateful purposes. The problem of fake news has been around for a long time. Whatever the reason for its creation, fake news is not only misleading to the public, but it can also have a negative impact on individuals, including defamation. As a news consumer and distributor, it’s important to be able to distinguish between fake news and real news to ensure that only real news is available to consumers. However, it is difficult for humans to manually analyse and fact-check news texts one by one, which requires a lot of human and time resources. Therefore, in the field, computer data analysis techniques such as AI and automated analysis are used to identify fake news. The fact that a computer reads and judges the text suggests that the difference between fake news and real news is in the text itself. Through this project, we will analyse the data of fake news and real news and visualise it in word clouds, pie charts, etc. to find out whether there are any characteristics of the text itself.

longer way to do a plot with more than one y value using the par function. by ephrage tapiwa rugara (ankara üniversitesi) > plot(x=coal$Year,y=coal$Value,type="l",col="blue",xlab="Year",ylab="Consumption",ylim =c(0,30) ) > par(new=TRUE) > plot(natgas$Year,natgas$Value,type="l",col="red",xlab = "Year",ylab = "Consumption",ylim= c(0,30)) > par(new=TRUE) > plot(nucl$Year,nucl$Value,type="l",col="green",xlab = "Year",ylab = "Consumption",ylim=c(0,30)) > par(new=TRUE) > plot(renew$Year,renew$Value,type="l",col="orange",xlab = "Year",ylab = "Consumption",ylim=c(0,30))

Importing and cleaning the eammi data set.

First course project.