Congratulations on launching and on the architecture choice and dev insights!
With regards to the product, there are several consequences you are about to see and need prepare to mitigate. I worked on something similar and need to rewrite it, thus the learnings.
1. The site looks like a dream come true for political recruiters/promoters. You have a place full of users self-identifying with political labels in great detail and you can reach out to anyone. You will see a ton of spam from companies, parties, surveyors, you name it. You may want to throttle it by limiting number of new people that can be reached by a user in 24 hrs.
2. Scammers or predators could bait people into in-person meetings or worse. All they have to do is mimic the typical profile of their targets. There is no verification of truth in others, but there is a lot of personal exposure of yourself.
3. It was strange to see people’s likes and dislikes as a profile. It gives you a lot to potentially dislike in a person, but nothing really to draw you to them as a person. In a community, the more preferences one lists, the more odds they have of alienating their neighbors, instead of bringing them together. Labels and stereotypes have one thing in common - they pidgeonhole people instead of giving them personality.
You have shown you can execute. The above is just feedback on the inherent intended or unintended consequences behind this new funnel for mixing people. Social products can be quite dangerous but also fun. It’s critical to reduce downside risk.
This is very good insight and I definitely agree. With regard to your first point, I'll look to add a limit to how many users a person can message per day.
I spent some time already and plan to spend a lot more on moderation tools to mitigate the effects of your second point. Ideally fake profiles can be both reported and detected, but as of yet I have not invested too much time into these efforts, other than adding basic reporting features and a moderation page for those with sufficient power.
I tried to mitigate your third point by only allowing users to see your total cluster vote as opposed to your individual card votes. As a result, there is a bit of plausible deniability as your vote for each card is somewhat masked by the average. This could be furthered by reducing the cluster count and thereby making each cluster larger and mask more individual card votes.
This is a total thought experiment and I have not thought deeply about it.
I wonder if you could encourage healthy debates by grouping people based on cluster, such that:
- Eveybody agrees with each other person in the group on the majority of topics.
- Everybody disagrees with the majority opinion on some topic(s).
- Every topic has two people who disagree with the majority.
- No two people share the exact same views.
I'm imagining probably 6-7 people per group. Make sure they know the matching rules.
Basically, I wonder if you could cut through tribalism and encourage nuanced discussion by making it clear from the beginning that everyone mostly agrees on everything, but everyone also has some points of disagreement. Then it becomes more of a "figure out where we disagree and why" type discussion. Maybe seed it with one topic in the center of the cluster that everyone agrees on, to give a "safe" starting talking point.
I could also see it devolving to a conformist atmostphere where nobody wants to voice their minority view, but I'm hoping that would be mitigated by everyone knowing that they all have a minority view, and that one other person shares their particular minority views.
On second thought:
4. I would go for specific leading topics for a person and leave clustering for the rest. Clustering removes the fine granularity you spend so much time voting on in the beginning. The cards also rely on gut instinct plus fat fingers - i found myself mis-swiping on several and didn’t really care to go back and fix them. Instead, you should allow statements of explanation behind the most pertinent topics or highlighting the most relevant topics after one is done swiping and then prioritize matching on those, with the rest lumped into clusters.
5. The topics do conflate two different mental systems and they clash badly: Interests are things you want to pursue more of together. Politics are divisive topics. You and I share an interest in building products that help people with niche interests find each other, we should be able to find each other with your product. Instead, we found each other with the HN discussion. That’s because depth and insights surfaces with content generated by the person, while swiping is low threshold but also too low signal and the gut instinct of one strongly opposing swipe would be to “skip” that person. If you want connection, let users focus on a few key topics to them and let them pick a few they definitely want to avoid in another person, then let people reach out based on your statements of purpose on a topic. If you want to dig into these problems over chat, call, or email, feel free to reach out to me at hnusername at dreamlist dot com.
5 The down side with people matching is the reason why there are no people marching IPOs out there. Once you are successful, you have to leave. The dating sites have all aggregated into one big company which is a cash cow. Don’t converge towards dating unless you want acquired and users churning massively. The interest matching is slightly different, in that a good match doesn’t preclude you from staying on the platform. The politics ones always turn into a dumpster fire, as political preferences can be fleeting based on your in-group. I would stick to interests for things you want to do together.
> I tried to mitigate your third point by only allowing users to see your total cluster vote as opposed to your individual card votes
I find these clusters really strange. For example, this cluster:
> War on Drugs, War on Terror, Fossil Fuels, Drone Strikes, Dark Humor, Military, Police Officers
And
> Yoga, Lower Drinking Age, Gym, Alcohol, TikTok
What does Yoga and Gym have to do with lowering drinking age, or with TikTok? Very weird. So if I create a profile and I am positive towards Yoga and Gym then people are going to think that I want to lower the drinking age? And likewise, they are going to think that just because I support having a military force (which I do), that I also support the war on drugs (which I don’t).
Would be better to not do clustering at all than to group a whole lot of unrelated stuff together and give the wrong impression I think.
So, the clustering situation is a bit of a double-edged sword. Here's the pros and cons I've found:
Pros:
1) Allows for instant similarity-searching. I am using the Postgres CUBE data structure to index users' votes and it has a limit of 100 items. So, if I didn't use clusters then there could only be 100 cards maximum, but ideally you would have even less than that because the CUBE can start to slow down when you approach that limit.
2) It's also a bit of a privacy feature as people can only see how you voted along cluster lines, and not how you voted on individual cards. This provides the aforementioned plausible deniability.
Cons:
1) Not all clusters are ideal, as you've seen. I spent a lot of time exploring different clustering algorithms and none of them were perfect. Some cards were naturally a part of multiple clusters and others didn't align to any at all. I'm sure a lot of this comes down to card choice, which I definitely could improve.
2) Can be confusing to users as opposed to just listing theirs and others votes on cards.
---
If you'd like to help and create better clusters, I'd definitely be open to tweaking them. Most of the required data can be found by navigating to the Cards page. For example, if you go there and click "War on Drugs" and then click "View Correlations", you'll find that "War on Terror" correlates the most with "War on Drugs". This data can then be used to try and create your own clusters. I've found it to be a very tricky puzzle satisfying all the constraints.
In the end, for performance reasons, I felt like I had to choose between either having clusters or only 50-75 cards, and I chose clusters. There's probably a better way of doing it, but I was unable to find it at the time.
Have you manually reviewed some of these clusters? Automatic clustering for subjective topics tend get gamed by users (if they can be influenced by users) or labeled incorrectly.
Yeah, the first pass for the clustering was SciKit's Agglomerative Hierarchical Clustering Function and then the clusters were manually tweaked in an attempt to increase accuracy. Clusters are also manually updated and curated, so hopefully they shouldn't be able to be gamed at the moment.
Upvoted:
People who take time from their day to give positive constructive feedback and encouragement to a total stranger about his/her project are what make this place a good community.
I was looking for a project to learn Rust with and improve my webdev skills, so I came up with the idea of Kardius. After reading The Rust Programming Language I began work on it. I posted it on reddit some months ago and tried to iterate on their feedback, so now hopefully it's ready for the big stage of Hacker News! (still very nervous though)
Basically, I had remembered Paul Graham's advice of "make something that you yourself would want", and I had always wanted a way of finding like-minded people around me. I had the idea for a website / app that let you swipe on concepts instead of people. For example, cards like "Hunting, Vaccines, Cities, Podcasts" would appear, and swiping right on them would mean you liked the idea or identified with the concept, with swiping left indicating the converse.
So, I made just that. It then uses the Manhattan distance formula to compute your similarity to others. You can also view statistics like the average swipe value for a card and how that card correlates with other ones (e.g. Hunting and Guns are highly correlated with each other).
You can then also view clusters of cards on profile pages. These are groups of cards with votes highly correlated with one another (initially found via SciKit's Agglomerative Hierarchical Clustering Function). You can then see how users align to these clusters. Another reason for clusters is because I am using the Postgres CUBE data structure to compute similarity between users, and CUBE caps out at 100 elements (and there's currently 250 cards). So to resolve that votes for cards are clustered into, well, clusters, and then the distance between CUBEs can be calculated, and this can all then be indexed for high performance similarity searching.
There is also the Interests page that lets you enter your individual interests. This is because not every interest can be a card as there can only be so many and the ones that do exist should be well-known and relatively controversial to give better predictive power. So, once the base similarity is established via swiping on popular topics, this page lets you tag yourself with whatever you'd like and then also search users and posts for these tags as well. There's also an interface on the Conversations page to easily keeping track of the latest posts for your interests.
In addition, you can privately message users and publicly create posts and tag them with whatever you'd like (examples: Rust, Hiking, etc.). You can also filter users and posts by date, similarity, age, and distance.
My backend dependencies are currently rand, bcrypt, serde, rusoto (for uploading avatars to s3), oauth2, reqwest, time, rocket, tokio, futures, deadpool (database connection pool), web-push, deunicode, async-stream, and pin-project-lite.
For Rocket I am using the async branch (recently merged to master, hooray!) and thus far it's been great. I'm extremely happy with it, both due to its technical merit but also because of the tremendous help the creators provide in terms of technical support. It was my first Rust project so I had a ton of beginner questions along the way and they were always extremely patient and insightful. The rocket server is currently hosted on a free-tier AWS EC2 instance.
For real-time messaging, I ended up creating a Server Sent Events library. It's basically just a channel that the multi-threaded Rocket server sends commands to (join this user to this room, send this message to this user or room, etc.). The library has a bunch of hash tables that keep track of all the rooms, users, and subscriptions. I also recently added support for an event log so users can temporarily disconnect and then receive all the messages they missed upon their return without having to refresh. If there is any demand for this I'd be happy to polish it up a bit and throw it on GitHub, as I'm sure my implementation is far from ideal.
On the frontend I am using React and... that's it actually. It's probably not the wisest decision (although I am kind of afraid of npm) but I ended up just creating minimal libraries for everything I normally would use a dependency for. My simplistic Markdown parser is around 150 lines, my Axios "clone" is just a small 100 line wrapper for fetch, my routing library is just matching the URL against my small list of path regexes and returning the corresponding component to render, etc.
Returning to the website's features themselves, I tried to make as many available as possible without logging in, as I generally dislike logging into sites, so no pressure to create an account at all! What I'd like more than anything is any suggestions or feedback that you might have, because I'm perpetually full of doubt and indecision on the proper course of action to take. Another thing I'm struggling with is marketing and actually getting it out there, as I know nothing of that world, and I always feel kind of weird about self-promotion. Anyways, thanks so much for reading!
First of all, thank you for detailing all of that and for sharing here. And for all the work you've put in to this! And secondly I wanted to say that this
> but I ended up just creating minimal libraries for everything I normally would use a dependency for. My simplistic Markdown parser is around 150 lines, my Axios "clone" is just a small 100 line wrapper for fetch, my routing library is just matching the URL against my small list of path regexes and returning the corresponding component to render, etc.
I'm glad you're a fan too! Yeah, vanilla Javascript seems pretty powerful these days. If you don't care too much about backwards compatibility or supporting really old browsers then you can get a lot done with really thin wrappers tailored to your use case. I suppose time will tell whether or not it was the right decision, but in the meantime I really like the peace of mind from not having to rely on npm.
The Kardius logo on the top left is very pixelated both on my phone and on my browser. Considering that the icons on the right are not pixelated I think this was not a conscious design choice.
Sorry for kibitzing, but I think this will impact people's first impression about your product.
I find the percentage-based swipe input distracting. I kept thinking how the exact number is going to affect recommendations and how that is measured relative to my previous inputs.
Consider showing two concepts next to each other so that swiping chooses one or the other, and swiping up chooses both.
Hmm, yeah, the swiping UX seems to be pretty tricky to get right. Initially I didn't have the percentage but some early testers highly recommended I add it for two reasons:
1) They couldn't see well and found the addition of the percentage was helpful in clarifying their swipe value.
2) It made it more obvious that the magnitude of swiping mattered, as opposed to swiping just being a binary yes/no option.
The two concepts idea is interesting. I'll have to think more on that. I think it might be tricky to implement though, because not every topic has a natural converse.
The code is really old and out of date, and was just a quick experiment, but that may give you some direction if at some point you want to try out that kind of user experience.
Unfortunately the demo link doesn't work anymore, but it should be quite easy to run locally.
Congratulations to the release! It's so refreshing, it's blazing fast, it doesn't load some stupid web fonts or other unnecessary things, I'd say it was worth the effort and would hope more websites do this. It just works :)
OK, I have tested a bit more. This is really interesting I took the time to answer all the question it asked me, and here is some more feedback:
- This thing needs anonymous sign up.[0]
- And a delete option.
- Also people needs to be nudged towards using partial names or pseudonyms and not full real names.
- You also probably understand this already, but you are now sitting on a heap of personal data already. This is really, really, really cool but also has the possibility to blow up relationships, families and generally create havoc. Lives have probably been lost over less than what is available here.
- answering all the questions was tedious.
- I want a clear way to vote "whatever" or "prefer not to answer"
- idea: Limit others view of your profile to what you are comfortable to share, like the facts that I: like card games, board games, CSGO, climbing. Leave out that I dislike Trump, liked Obama, still support the 2nd amendment, support decriminalization of marijuana etc etc.
- crazy idea: create linkable public profile with the things I want to share (like above) so I can link to it from my profile here for example.
[0]:You then probably need another way to reduce scammers/spmmers ability to create multiple customized accounts to target/befriend people.
I have tried out several of these services before in a way to finding new friends but 99% of them is filled with people that actually are more interested in finding a date instead of a mate.
Right, that is a very good point. That reason is why I neglected to add a gender option, as I felt the inclusion of that filtering criteria would steer the culture towards that of a dating site.
As for its reason for being, it's mostly because I just think it's a bit of a shame how there could be this awesome person down the street or in my city, and I could live my whole life without finding that out. I was hoping to develop a service that might alleviate that.
For example, if you were into some obscure Steam game, you could specify that as an interest and potentially see that someone else near you also shares that interest as well. You then might message them, play together, and then if you hit it off some time down the line you could eventually meet in real life as well.
Yeah, but in order for your project to be successful in that way it would have to mean that a lot of people need to sign up.
I live in a rural area in northen europe, they chances of this site becoming big enough for it to be interesting for me are very slim. Of course I could find internet friends through it, but that's not what the site claims to aim to solve for me.
I don't want to be negative, but I think the most common first question will be what gender people are since that info is missing. People will just go around whatever obstacles exist in order to date if that's what they want. I would suggest instead of having a separate dating section so those people will fill up there instead.
Dating and sex also sells and could help the signups along the way.
I tried it out, and immediately regretted it! I didn't come up with any matches, and then realized I provide a lot of personal details, and got nothing in return. I can't find any information requesting how to delete my data, though.
I like the idea, but would really appreciate some information on how to get my data deleted.
Yeah, a lot of people have been requesting this. In the interim you can go to the Cards page and click on cards and change your votes there to baseline. This has been a heavily requested feature though and I'll be adding the ability to reset your votes and delete your account this week.
Should be added now if you refresh your profile page and click "Account Settings" there. I've added a feature for resetting all your votes and deleting your entire account.
The website is nice and easy to use and the concept is fun. I love hierarchical clustering so the technology also appeals to me. But I was very disappointed by the nature of the cards, I expected hobbies or personality based card whereas almost all those I got were about political issues. Who chooses their friends based on their opinion of Brexit? That seems very unhealthy. Maybe I was unlucky.
Another thing is that even for non-political topics. The clusters that are drawn end up being political. You like anime? -> Libertaniarism cluster. You like research? -> Free speech cluster. If you dislike Libertaniarism suddenly you no longer match up with people who like Anime. That's the danger of unsupervised learning, it might be interesting to impose some constraints on it so that you can control which topics get compared together.
This is actually something that I'm still trying to figure out, and hopefully can be improved in the future. Maybe you can help me out:
So, the problem we'd like to solve is what set of 250 or so cards has the highest predictive value in that similar answers lead to the best interpersonal matches?
The problem with hobbies is that there are so many of them and not many people feel very strongly one way or the other about many of them. You probably wouldn't not give someone a chance just because they prefer ping pong to pool, for example. Rather, I was looking for what might be deal-breakers.
The Interests page and tagging in general is what I am hoping will fill that need of specifying your individual interests and matching based on them. Here is where you can tag yourself with whatever you'd like and then search for users and posts based on these tags. The card swiping's function is mostly just a first-pass elimination filter.
I had the thought of perhaps doing categories instead with regard to cards. For example, sense of humor is often very important in people. Perhaps 50 of the cards should be memes? And then perhaps 50 of the cards be political, 50 of the cards be hobbies, etc.? Or perhaps there could be multiple similarity percentages, each of a different category? It's still very experimental and I'm not sure what the correct path is.
In the past I've been very isolated because of health issues which kept me in bed for months at a time, and I've thought a lot about how to make friends online. I've come to the following conclusions:
1) You need a common topic of interest to start the spark of friendship, something that keeps you coming back and gives you an excuse to speak to each other and unending content to speak about.
2) You need to force yourself to check up on them daily to weekly about that topic.
3) You need them to be interested in forming a new friendship (it's a lot of work for both parties involved, not everyone cares to extend their circle of friends or to form online friendships).
4) You need chemistry.
5) Things are a lot easier if you belong to a small online community where people know each others.
Among these 5 requirements, (2,3,5) are irrelevant to your problem of matching people.
Requirement (1) you can provide through hobbies/interests card and clustering somewhat easily with the current system.
Requirement (4) I don't know what it is, or what makes it work. With some people it just won't click. I know it's not because of opposite political beliefs, or lack of common interests, because I have friends which are counter-examples for those potential failure cases. I think it has to do with personality, similar thought patterns (not beliefs) or something like that. The categories you mention could be a path towards quantifying that but you'd want them to be soft-indicators because again people with opposite political beliefs, or senses of humour can be great friends. So I don't really know in the end.
Have you looked at online dating research? I bet there's some smart people who worked on compatibility indicators for these kind of applications.
(Forewarning: I haven't had a chance to check out the site yet this is purely based on what I've read in the comments so far) I would also say some hobbies are good to add, just don't be to narrow on it. While pool or ping-pong might not be good so broad topics like watch sports, play board games, video games, (biased) anime. Broad topics like that are typically what I'll discuss with friends even if our specific interests in the topics don't align.
I think the right type of thing are the sorts of questions that get put in buzzfeed lists like “10 questions to find out if your date is the one” and “how compatible are you? 25 questions to predict relationship success with your partner” type things.
The questions are all like “do you like camping”, “would you like to live in a foreign country” etc.
Some questions like this have actually been studied for their predictive ability I think.
> So, the problem we'd like to solve is what set of 250 or so cards has the highest predictive value in that similar answers lead to the best interpersonal matches?
I think ideally you should somehow allow users indicate what kind of "interpersonal" similarity they are looking for. Perhaps right now I want to find intellectually similar people -- but maybe later I want to find people with the same sense of humor. Hell, maybe I just want to find people interested in eating the same food.
Here's an abstraction that I think could be a killer feature, and could solve a lot of "problems" around matching, privacy, etc: Cardsets.
A cardset would be a set of cards with its own theme. My answers to the cardsets can be hidden/shown at will. I can view similar users based on responses to a single cardset, and my "overall matches" would be a weighted similarity across all cardsets, where I can toggle how important each cardset is.
So now imagine the following cardsets:
- Politics. Swipe left for "bad idea", right for "good idea".
- Humor. Swipe left for "not funny", right for "funny".
- Food. Swipe left for "disgusting", right for "delicious".
- Aesthetics. Swipe left for "ugly", right for "beautiful".
- Hobbies.
- Activities I want to try.
- Places I want to go.
- Fashion, technology, programming, ...etc...
I can now find people that have similar fashion taste to me. Or that want to travel to the same places as me. Or that like the same food as me. There's also the nice side effect that I don't have to swipe on cardsets I don't care about, and that there's a lot of swiping I could do, which is potentially fun. Sky's the limit here!
Furthermore, if you want to get "advanced", add a way for me to find "custom matches", by which I weigh the importance of each cardset. Perhaps I want to find people that match based on "Politics" and "Humor" ... so I'd set those as having high weight and the others lower.
You now have a channel by which you can add endless amounts of content, and can iteratively improve your matching and engagement. Adding a new cardset opens up an entirely new set of matches to all of your users, and gives them something to swipe.
I think this concept is extremely powerful and valuable, and opens up endless avenues for future growth. Imagine brands being able to fill out cardsets for "aesthetics", or "food", etc. Now you can match users to brands they care about.
Lastly, to light a fire under your ass, if you don't commit to doing this, I will. The more I think about it, the more I think this is something that could catch on, especially if you let users create cardsets and add other viral features (eg: ability to send a link to someone to fill out a cardset to find out how much they match me).
Another fantastic reply! I really need to get this to take off already so I can hire you before you make your own and out-compete me.
The more I read this reply, the more I agree with it, and I think it may actually not be that difficult of a change. Card sets could be integrated into the existing cluster concept and I could just give users the ability to choose which sets (clusters) they swipe on and the weighting that they apply to each. They could also decide which clusters should be factored into their similarity matching. I _think_ this will all work with the existing CUBE concept, which is exciting, because many other proposed solutions by others didn't fit nicely within that mathematical structure.
You've honestly given me a lot to think about and I think I see a better way forward now. Your insight really increased my mood because I think you've discovered something very important that I am likely going to be spending quite a bit of time on in the next coming weeks and months.
I would advise against folding it into clusters, and instead have each cardset be its own thing. What you have right now is a cardset that I'd label "General" -- abstract the backend so you can create different sets of cards ("Food", "Fashion", etc). If manually curate cardsets, you won't even need to worry about clustering. Yes, it's a shame you spent time on it, but no clustering will ever beat manually creating sets of cards.
In terms of producing a "total match score" with a user, you compute a match score for each cardset that both users have, then use a simple normalized linear combination to get the total.
If users A and B have cardsets X Y and Z in common, you would produce similarity scores "S" for S(A,B,X), S(A,B,Y), and S(A,B,Z). Then, you use the weights that user A selects for each cardset (W(A), W(B), W(C)), normalize such that they add up to 1 but maintain their ratios, and compute total similarity of A matched to B as: W(A) * S(A) + W(B) * S(B) + W(C) * S(C).
As long as you have pre-computed the scores between all user-cardset pairs (your scaling pain point), computing match scores even with weights is trivial and fast.
> You've honestly given me a lot to think about and I think I see a better way forward now. Your insight really increased my mood because I think you've discovered something very important that I am likely going to be spending quite a bit of time on in the next coming weeks and months.
Happy to hear. I've been working on my own project for close to a year and am close to launch, so I think I understand where you are coming from.
It is practically impossible to view your product as someone unfamiliar with it would. So, that leaves you asking for feedback. Next, it is really difficult to distill user feedback (such as found on this thread) into things you should actually work on. Is a comment just a vocal minority complaining or an indication that some concept should be changed? I think you're doing a good job taking feedback to heart and I'm really rooting for you.
> Another fantastic reply! I really need to get this to take off already so I can hire you before you make your own and out-compete me.
If/when it takes off, just make me an adviser and shoot a couple percentage points my way!
Should be added now if you refresh your Profile page. I've added an Account Settings button that lets you reset all your card votes and delete your account and all its data.
To be honest, what I am most interested in, is how you got the people to actually care. So what exactly did you do for marketing? Did it just work, or how exactly did you achieve initial traction?
Haha, this is actually still an open question. My marketing thus far has been exclusively just posting it on a couple subreddits and this Hacker News thread. I don't think I've yet achieved traction because there aren't enough users to sustain interest so most people get bored pretty quickly and log off, but I'm working on it! If I figure this out I'll let you know though.
I spent 20 minutes swiping on topics I don't care about. There were only 5-10 cards that I really cared about and they are being drowned out by stupid Brexit cards in the similarity score.
i could see a closed version site like this being useful for reigonal or comminity development projects, as a supliment to the "find out what everybody wants to do" workshop phase.
This website has a bug in the chat where if I type too much text and it goes out of the box, the entire webpage goes blank and the page throws a react error. lmao
In the beginning it was a bit tricky because the migration to async was happening within the Rust community, so that caused some code churn early on. Lately though it's been smooth sailing.
I'm using tokio-postgres for my database library and both it and Rocket are async, so they synchronize very well together. I do not believe Diesel is currently async, but in either case I'm using tokio-postgres instead so I haven't had to look into how to integrate Diesel with Rocket.
Other than that, my needs were pretty simple and I used well-supported platforms, so I haven't really run into any major issues yet.
Firstly, congrats on the launch. Designing and implementing a new concept from scratch, by yourself, is definitely fraught with difficulties. It's hard to know if what you're designing is "right" and if you're implementing "the right way". Sticking with it for an entire year and actually launching is definitely something you should feel good about.
I think this is a great idea, and for a first version the execution is actually quite good. Once I figured it out, I enjoyed using it and flew through all of the cards. I looked at a lot of matches and even sent a few messages. Overall, I can see myself coming back for random chats from time to time.
Here is my feedback, in order of what I perceive to be most important.
1. It was not at all obvious to me how to swipe. I tried swiping the card but it didn't move. So I clicked the arrows. Since I "agreed" with the first 4 or so cards, I did not realize the arrows were to go back and forth. (In fact, I would not have ever expected back and forward to be an option). Then I realized that the "help button" thing was actually how to slide, and I got it from there.
I suggest you make the slider thing look "slideable" and obvious that left is disagree (red), right is agree (green). Right now, it definitely is easy to see it as a "help" button.
I also suggest you make the card navigation arrows not ambiguous -- I think it is fair to say people will assume they mean "agree" and "disagree" rather than "next" and "prev". Either provide context so that it's obvious what they do, or use words "next", "prev".
Here is a crappy mock-up that hopefully shows what I mean: https://jsbin.com/wekuzebasu/ - In this shows progress and is obvious what next/prev do, and (for me at least) it is much more obvious what the call to action is, and how to operate it. (You could replace "|||" with "<->", or show arrows next to the slider circle for even more emphasis).
2. I really love the "percent" agree/disagree. I think that's way better than just "yes/no" and it greatly increases my confidence that I'll get better results.
3. I think your initial card set is actually quite good. There are a few where it is ambiguous of "left" and "right" mean. Agree / Disagree?Like / Dislike? Support / Don't support? Care / Don't care?
4. If I were you, it would be very easy for me to worry about spam/abuse/gaming of this. But, honestly, your biggest problem will be overcoming the network effect to get a critical mass of users to make this better. If for an average user there are more similar people, and they are closer, it becomes much more compelling for more users to join -- leading a virtuous cycle. If you want this to catch on, your #1 concern should be getting the most users in the least amount of time.
Handling spam/abuse is a problem you want to have, and I'd put it off until it's necessary and/or until it's clear it is slowing user growth.
5. I've read all of your comments, and I think you're making some very good decisions and are putting a lot of thought into this. I hope you stick with it.
6. The clustering is good and does provide some level of "privacy" -- though for my "similar" people I often do not see any clusters at all. Anyway, this seems like the type of app where I want people to know my opinion on stuff, and if there's a question for which I want my opinion to be unknown, I'll just skip it.
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Now a question regarding the matching. Is there a difference between "unanswered", "skipped", "0% (as opposed to -X% or +X%)" ? Consider these cases:
1) I don't care about a card. This is distinct from being "0%" -- I don't want this card counted towards producing my matches. If someone is 100% or -100% on it, don't penalize the similarity.
2) I am neutral about a card, but I do care if somebody is +/- on it. Do consider this in similarity.
3) I have not answered a card. This should not count towards similarity.
4) I previously had an opinion on a card, but now I don't care. How do I "reset" it?
Depending on how this is handled, you'll need to change the UI to make it more clear. Eg, you may need a "skip" button.
Wow, this is an incredible reply. Thanks so much for such an in-depth analysis and compliments!
I actually really like your mock-up and really appreciate that you took the time to make it. Hopefully you don't mind if I take quite a bit of inspiration from it, because I definitely think it looks much better than my current one.
Yeah, I agree that the network effect is one of the biggest problems. Retention seems very tricky with a concept like this because while posting it to reddit or HN can result in many registrations, few people stick around because there isn't much to do on the site because there's so few users at the moment. It honestly does make motivation pretty difficult, but I am indeed going to stick with it regardless.
With regard to your last 4 numbered points, currently 0% == not answered == neutral, and this is mostly due to technical limitations. Your default similarity cube is just (0.0, 0.0, 0.0, 0.0, 0.0, ..., 0.0) (50 zeroes), and voting on cards adjusts this accordingly. Such that if you answer 100% to every card in the first cluster and answer no other cards then your CUBE would look like (1.0, 0.0, 0.0, 0.0, 0.0, ..., 0.0)
I was thinking about a potential way to solve this, but as of right now due to the constraints of CUBE similarity matching, this is the current solution.
Regarding the 0.0/default/skipped -- see my other response about "cardsets", which the more I think about it, the more I am convinced will solve nearly all of your issues:
- you don't have to worry about the skipped vs neutral problem (as it is fair to expect a user to answer all cards in a cardset).
- you don't have to worry about clustering. a cardset is a "cluster".
- you can work around technical limitations by having each cardset be its own cube
- you boost retention by being able to have a library of dozens of cardsets (rather than 250 cards). limitless swiping, and swiping on things that your users will find interesting because they are selecting cardsets that are important to them.
- you can make your site viral by allowing users to send a link where the receiver can (anonymously) swipe all the cards of a cardset and see their "similarity" to the link sender. (Then you can ask them to register to be able to send links themselves).
- futures paths for revenue are endless
I think you are 100% right here. Wow, thanks so much. This really is amazing. I'm going to begin work on this soon (just need to get some sleep first!)
Also there is another aspect to cardsets that might be worth thinking about, which is that they are like "polling" done in a fun and easy way (swiping on pictures) -- the fact that you can also show people that answered similar to me doesn't need to be the focus.
Having polls like this can help you grow the site. For example, imagine I make a cardset for "Beatles albums" where I put in each Beatles album, and shoot the link out to, say, r/Beatles or whatever. Your site can let people swipe, then show the aggregate % for each of the cards, thus ranking them.
Of course... having viewed this really fun and quick poll, random pollers might wish to make their own new polls and spread your site.
Enjoy your sleep.. you have a long journey ahead of you!
With regards to the product, there are several consequences you are about to see and need prepare to mitigate. I worked on something similar and need to rewrite it, thus the learnings.
1. The site looks like a dream come true for political recruiters/promoters. You have a place full of users self-identifying with political labels in great detail and you can reach out to anyone. You will see a ton of spam from companies, parties, surveyors, you name it. You may want to throttle it by limiting number of new people that can be reached by a user in 24 hrs.
2. Scammers or predators could bait people into in-person meetings or worse. All they have to do is mimic the typical profile of their targets. There is no verification of truth in others, but there is a lot of personal exposure of yourself.
3. It was strange to see people’s likes and dislikes as a profile. It gives you a lot to potentially dislike in a person, but nothing really to draw you to them as a person. In a community, the more preferences one lists, the more odds they have of alienating their neighbors, instead of bringing them together. Labels and stereotypes have one thing in common - they pidgeonhole people instead of giving them personality.
You have shown you can execute. The above is just feedback on the inherent intended or unintended consequences behind this new funnel for mixing people. Social products can be quite dangerous but also fun. It’s critical to reduce downside risk.