Analytics Case
Tell us how you would estimate how much fake news is there on Facebook. How would you estimate its impact?
Data Scientist
Meta
Mollie
Ubisoft
Huawei
Benchling
Answers
Anonymous
5 months ago
Clarification -
- What is defined as fake news?
- Why does it matter?
- Impact to what? User retention? user engagement? Acquisition rate?
Let's define fake news as posts from new users who create a large amount of content and have low friend count & friend invites. Offer to define "new" & "low" if interviewer wants you to spend time there. If this is a brand new definition, start small and have human review to validate that definition is in fact reasonable.
Let us consider only US created posts that appear in the newsfeed.
Let's say the impact we prioritize is user engagement. Few metric options:
- login freq or
- total time spent on newsfeed or
- Total time spent on FB
- User activity i.e. reactions & comments
Pick one.
Check if the selected metric is co-related to how many fake news posts appear in their news feed?
Segment this by user type (new vs established)
Anonymous
4 months ago
Look at how many posts in the news category gets tagged as spam or reported. Also look into the virality, as fake news spreads faster. Impact could be estimated by tracking bounce rates when this news is viewed or number of reports as scam. also look at churn rate
Anonymous
5 months ago
- What isfake news:
- News that have inaccurate/incorrect information
- User/page generated, shared from other platform
- Or created by anti social groups, extreme groups with agenda
- Impact:hurt credibility of information
- discourage user from engaging
- churn in the end
- Identify fake news: Users reported fake news:by number of reports vs probability of fake Sample posts and do manual screening by agents For posts that do not have reports, find proxy: sensitive keywords, unknown source stratified sampling, Existing labels - build a classification model
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