Luna’s last major promise is to use cutting-edge machine-learning techniques to come up with a good match algorithm: Despite significant technological advances in information processing, storage, and retrieval, online dating has yet to optimally integrate machine learning for the user’s benefit.
A typical ML task for online dating might be to predict the level of compatibility between two users from a given set of input data, thus predicting for example whether one user is likely to respond to another user’s message […] Luna may adopt a collaborative filtering algorithm developed by Dr. In addition, Luna may use advanced NLP techniques in conjunction with IBM Watson to integrate additional information from the contents of messages sent in-app, as well as from social media sources such as Twitter, if users choose to provide that information.
Stars can be bought with dollars and vice versa, so popular users can actually earn money reading all the messages sent to them. Market forces are the known solution to the problem of connecting resources to their highest-value use.
In this way Luna’s financial incentives will be aligned with users’ goals at Stage IV in the exchanging of messages. Possibility of tipping in case of successful offline dates.
Another way to provide incentive for Luna to help achieve its users’ goals is to allow users to tip the platform after the achievement of Stage V in the completion of a successful date.
As described in 3.2.4, we intend to make feedback polls available after dates.
Tipping a platform is an infeasible idea in the context of currently existing dating apps; however, the free and direct-to-user benefits of Luna may register to users as something more resembling the mechanisms of Wikipedia: a free, friendly, and user-contributed service, rather than a platform like Match.com, which can feel exploitative.
A tipping option may thus encourage a feeling of alliance with Luna in the user.