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OK To begin with I am not sure if what I am about to do violates the do not spam or refer to But when I saw this, the following thought occurred to me.

Imagine that there exists a cyber hostess. That is, resident within any online community there existed an entity that knew everything relevant to that community about everybody in the community. This all knowing person could provide introductions based on mutual interests and preferences.

This is not a yenta. That is, it would not be a dating site, thought it could be. But because this hostit (not a host, and not a hostess, but a hostit?) knew people, it would have a good idea of who would click and who would not.

I think that I can do that for any community. I would of course need some help. Is there any interest in this?

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This idea from —an opt-in, community-resident “cyber hostess” that surfaces useful introductions—can work if it targets specific, measurable use cases (mentoring, onboarding, project matchups, conference meetups) rather than trying to be universal. is right that moderators already play this role; the automation should reduce their workload and produce trackable outcomes (time saved, acceptance rate, retention lift) rather than replace human judgment.

Key design and legal constraints: collect only what is necessary, use progressive profiling, and make clear how answers will be used. Avoid inferring or exposing sensitive attributes (health, religion, sexual orientation) without explicit consent and expert review. For background on people disclosing differently to computer interfaces, see . For legal framing, see the EU GDPR text.

Practical matching approach: combine explicit tags (skills, interests, goals) with behavioral signals (shared groups, past interactions, response history). Start simple and iterate with A/B tests. Example scoring to tune in an MVP:

score = 3*tag_overlap + 2*shared_groups + 1*interaction_freq + recency_bonus - blocked_factor

select top N candidates where mutual_consent == true
send warm_intro_template; track intro_accepted, conversation_started, retention

Operational workflow: launch an MVP “Introduce me” button, require mutual opt-in before contact, provide warm-intro templates, and keep a human-in-the-loop for the first waves. Instrument acceptance rate, conversation conversion, moderator hours saved, and abuse reports. Conservative defaults, transparency about matching logic, and easy opt-out/delete controls keep the feature useful and trustworthy.

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The owners and moderators of many online communities perform this role. I have done it myself with the few communities I have created throughout the years. It does take time and work. Sometimes its appreciate and sometimes it is not. You got to think of that as well, especially if you are looking for a ROI.

Member Avatar for factotum

The owners and moderators of many online communities perform this role. I have done it myself with the few communities I have created throughout the years. It does take time and work. Sometimes its appreciate and sometimes it is not. You got to think of that as well, especially if you are looking for a ROI.

Computers are better are better able to predict serious suicide attempts in mental patients for two reasons.
1. they are not afraid to ask the hard questions
2. people are more likely to answer personal questions that are asked by a computer than by a person. Silly I know since a person will eventually read those answers, but people are people

In any case, my system can ask more questions, more personal questions, and probably get more honest answers Also my system is not emotional and can be tuned and fixed

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