Honours Project - Fake News Detection 4th year of Business Information Technology at Edinburgh Napier University
This is the source code and data for my Honours Project conducted 2019/2020 at Edinburgh Napier University. The project was concerned around the topic of fake news detection on the internet. Additionally, a survey among 164 participants was conducted to gather data on people's news consumption behaviour and their experience with fake news on the internet. Participants were asked to categorise six news headlines into the categories of fake and real news. Several machine learning classifiers have been trained and made predictions on the same six news headlines. Thereafter, humans' and the software's effectivity of identifying fake news were compared. Lastly, recommendations for social media platforms on how to handle fake news were created based on those results.
If you want to view the source code and the respective outputs/ results: -> open Honours Project - Fake News Detection.html or Honours Project - Fake News Detection.pdf
If you want to run the code: -> download/ install Anaconda (Python 3.7) -> https://www.anaconda.com/distribution/#download-section -> open Anaconda and launch Jupyter Notebooks -> open Honours Project - Fake News Detection.ipynb -> run each cell manually by pressing the RUN button or go to Kernel -> restart and run all (note: might take ~2 hours, feel free to comment out lines) -> depending on where you stored the csv file (data set) you might have to change the path in the code (should not be the case if you just unpacked everything as is)