Data collection, cleaning, and model training
There is a growing trend of investigative journalism on Youtube. The channels that perform this public service include: CoffeeZilla, Tom Nash,Barely Sociable and others.
I came up with the idea for this project as a way to supplement the activities of these Youtube creators with community-driven research and discovery of interesting/strange/outlandish/suspicious channels on Youtube (and other sites).
The following is a list of Youtube creator channels that may or may not match the classification known as "fake guru" which is based on a shortlist of niche content producers. Names are in this list if the trained deep learning model classified a majority of video titles as matching a "fake guru" pattern. Not all creators here are fake gurus, this is because the convention used by fake gurus to name their videos is a sort of standard across Youtube (ie Clickbait titles) so it's a challenge to seperate click-bait from fake guru. :) Also, some people that appeal to young people and flash cars may not be considered fake gurus by the general definition of "overpriced mml seminars etc." but may match the lifestyle/brand in other ways.
At first I thought there would be a wealth of names on the CoffeeZilla playlists. I used SPACY to try to extract PERSON entities but it's not very good and extracted many random names and mistook name of non-persons for PERSON type. So this is a work in progress for sure. Perhaps such a list could be used in the future to improve the model.
names mentioned on CoffeeZilla
Keywords to use to find fake gurus fast
feel great make money drop ship love life