文件列表:

TEXTMINING_FAKE1.R
TEXTMINING_TRUE1.R
TOPIC_MODELLING_TRUE.R
mktg_text_mining1.pdf

# TEXT-MINING---REAL-VS-FAKE-NEWS In this project, I have analysed two datasets real.csv and fake.csv, which have been curated from several thousand news headlines from around the world. The titles are labelled as real (indicating that they are valid news articles) and fake (representing fake and propaganda news articles) from spurious internet sources. My primary goal here is to use Text Mining as a tool to identify the differences that can help someone understand how real news headlines differ from fake news headlines. I have used UDPIPE and RAKE methods of unsupervised analysis to study the actual words that are in the headlines, to develop the foundations of building a classification model out of it.

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