What factors would you look at to come up with people you may know algorithm?

What factors would you look at to come up with people you may know algorithm?

Can you tell us which variables are most significant in determining potential recommended connections for a 'people you may know' feature?

What factors do you think should be prioritized when implementing a 'people you may know' program to optimize the suggested friend feature?

What are the primary data sets or inputs that would contribute to creating an effective algorithm for suggesting friends on social networks?

How would you consider social interactions, such as mutual connections, in developing an algorithm to suggest potential new contacts to users?

What criteria would best balance the importance of different information sources, such as role titles versus hobbies, in building an effective 'people you may know' algorithm?

What methods would you recommend to identify weak ties and facilitate building stronger connections in a 'people you may know' tool?

What kinds of machine learning or predictive algorithms could be applied to accurately recommend connections to users in a 'people you may know' feature?

What role would user feedback and interaction data play in optimizing and refining an algorithm that suggests friends in a 'people you may know' feature?

What are some key elements that would be considered in devising an accurate 'people you may know' algorithm?