
'Likes' are a Flawed Currency - robotmay
http://blog.photographer.io/posts/2013/05/26/likes-are-a-flawed-currency/
======
programminggeek
Likes are not meant to be a currency at all, it's meant to be an engagement
tool with minimal friction. It's not about ranking anything, it's about making
it so easy to say "check out this cool thing I found" that anyone can do it.

Anecdotally, I used to surf the internet a lot in high school in the late
90's/early 00's and not a ton of my friends were online, so there wasn't much
shared link wise among us. Then, in college, there was a group forum that a
bunch of us were a part of and one of the more popular parts of it were the
links people posted. Then, after college digg, Facebook, reddit, pintrest and
twitter all found a place amongst the population at large for sharing things.

I guess for most people sharing is not about currency or ranking at all, it's
about sharing something interesting. It's more akin to telling a friend about
music that you like, a book that you are reading, or a newspaper article you
thought was insightful. When you think of those things, it is rarely about
ranking them, it is almost always about sharing.

People share with other people because it makes their life better or their
friends' lives better. They do it because they care about their friends, not
because they care about you or what you created.

------
eterm
I agree they are a flawed currency, I don't agree on your solution.

Not only is 10 an arbitrary number, but it sounds like a lot less than some
people would like to give, and a lot more than most people will give any way.

Why not have the best of both worlds by using a PageRank-alike system to
determine the weight of any given like.

That way, if someone is spamming likes they won't affect any one item very
much compared to someone who likes only sparingly. You can go the whole hog
and have the system where heavily liked users are more powerful than non-
heavily liked users also.

~~~
robotmay
I have considered more complex systems (i.e. dynamically altering the value of
recommendations) and it's something that's likely to feature in the future.
However I needed a simple solution for now whilst the site is developing, and
I took a rough stab at it!

I'm very likely to adjust the limit (if not alter the system in the future)
based on how it's used, but I'm waiting for more data before I make that jump
:)

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btilly
It seems to me that the problem here is not that likes mean the wrong thing,
it is that the developer wants to post-process likes to create a metric that
means something and it isn't working out to what it desired.

The simple solution is to post-process likes in a different way. See
[http://www.evanmiller.org/how-not-to-sort-by-average-
rating....](http://www.evanmiller.org/how-not-to-sort-by-average-rating.html)
for a suggestion that makes them more like a rating, despite the fact that
some people use them differently than others.

But we can do other things. Here is a fun one. If a person likes 2 different
photos, we can say that is a connection between them of strength 1/log(#
photos liked by that person). The total connection between any two photos is
the sum of the connections. From each photo we can now find other photos that
are in some sense likely to be liked by people who like the first. People
enjoy following connections like these.

This system is similar in principle to the one that I wrote about at
[http://bentilly.blogspot.com/2011/02/finding-related-
items.h...](http://bentilly.blogspot.com/2011/02/finding-related-items.html).
Which drove a noticeable sales bump.

So the challenge is not to remove likes as a mechanism because it doesn't give
you the information that you want. It is to find ways to process the data you
get from it to pull out useful information.

~~~
robotmay
Thanks for the links; I'll definitely be reading through those later (as this
field is very interesting to me)!

I think I may have confused matters somewhat by comparing directly to a
'Like', which is more like a 0-1 rating system, rather than to a combination
of Liking and Sharing. How far it goes towards each of those is something I'm
experimenting with :)

> Here is a fun one. If a person likes 2 different photos, we can say that is
> a connection between them of strength 1/log(# photos liked by that person).
> The total connection between any two photos is the sum of the connections.
> From each photo we can now find other photos that are in some sense likely
> to be liked by people who like the first. People enjoy following connections
> like these.

I can't wait until I have more data to play with and I can start experimenting
with ways of connecting photos like you say; I've not often had the chance to
try out some of these ideas due to the limited size of datasets I've had in
the past.

------
captainchaos
I disagree. Considering the way likes work on platforms like Facebook, by
Liking something you are advertising your interest in it. Viewers of your
profile can see (and judge) the things that you have liked and also you create
a story visibls to you friends in the ticker when you Like something. I know
some of this is inherent to Facebook, but similar features likely exist on
other platforms as well.

Capping it artificially stifles users who may actually enjoy photography more
than others. A critic would presumable like photos far more often than a
casual user.

~~~
perlpimp
I agree, saying likes are a(or resemble) currency is dubious preposition at
best. FWIW likes as an idea is distorted, there are no unlikes so meaning you
have no likes proposes that you have dislikes - except that you don't have way
to measure disapproval. Consequently if you would be deprived of likes it
would not devalue your work in most but most of the extreme cases.

Likes don't deliver any serious value to all but the most popular of internet
celebrities. They do feel good though but you can't pay rent with likes.

IMO YMMW.

------
tmuir
Likes on facebook are a seriously heinous currency.

"Please like us on facebook to unlock this functionality of software that you
thought you already had full access to."

"To enter this contest, like us on facebook."

Now, the number of like's your product has is completely uncorrelated to the
number of people who actually "Like" your product. You are effectively saying
"look at all of these people we convinced to arbitrarily click a button"

------
RyanMcGreal
Not complicated enough. I propose a cap-and-trade system for Likes.

~~~
Nursie
Like.

------
nickm12
There is certainly negative pressure on likes. For well meaning users, likes
reflect what you like, which means they reflect you. In the case of Facebook,
the platform also advertises what you like to others.

People are strongly motivated to look good in the eyes of others, so most
people don't like everything, that's just creepy.

~~~
greenmountin
Are you sure FB doesn't rate limit the exposure of your likes to uninvolved
parties? I am too stingy with likes, but have fantasized about going bananas.

~~~
disgruntledphd2
With Facebook, nobody gets your likes (well except for your friends, or any
Pages you like).

You can, however, as an advertiser target people who "like" particular things
but you don't find out who they are (unless they click off site and sign up
for your service).

------
RandallBrown
Liking _does_ cost me something.

It alerts everyone that I'm friends with that I "liked" something.

I'm not going to go around handing out likes for things because it will make
me seem annoying and not genuine. I also don't want to represent myself as
someone that likes Wal-Mart or Samsung unless those are things I actually
like.

~~~
robotmay
I handle this slightly differently in that your recommendations are not
publicly browsable, and should they become so then that will be disableable by
a configuration option. I very much want to use it as a method of exploration,
rather than advertising.

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saidajigumi
The way TFA puts the matter, this looks like an Information Retrieval problem.
That is, the author is looking for a data stream that can be used to inform
search relevance. One might imagine collecting other active or passive metrics
(e.g. "click through from thumbnail", "time on page", "times shared") to
inform relevance as well.

Another question I'd pose: what's the real goal of a "like" in the various
contexts it is used? In many Facebook applications (e.g. liking a photo,
comment, etc.), it appears to be as much about filling in missing social
cueing -- a one-bit emoticon, if you will -- than about informing relevance.
In other contexts on Facebook, there's a definite notion of relevance (e.g.
liking a page).

Given that, I suppose I must ask: how much additional value can really be
added to this single low-information stream vs. simply using additional active
or passive metrics to inform relevance? Is "like dilution" really such a big
problem? If it is, there are other approaches to consider.

Instead of creating artificial scarcity it may be worth using another IR
technique and inverse-weight a signal based on dilution criteria. I.e. if one
user expends LOTS of "likes", they effectively place a lower value on each of
those. If another user uses "likes" very infrequently, we can infer those
carry more weight. A straw-man example: turning the proposed technique on its
head, the summed _value_ of a user's likes might be capped at 10 points each
[week, etc.], with no limit on the number of likes. The value of any like
within that window is 10/[number of likes this week]. Users can click the
"recommend/like/etc" button as many times as they want, and the system will
dutifully record and interpret that data according to the site's needs.

~~~
robotmay
Great feedback, thanks!

Your last paragraph is something I've been considering as a next evolution of
how it's implemented, but I'm waiting for more data (and time!) before I take
a look at developing it further :)

------
PaulHoule
There's an interesting idea here, but it takes some teasing out.

For one thing we need to pin down the word "like", which means something
specific on Facebook and often something different in other places unless
those places are playing the Facebook like game.

My gut feeling about social is that it a game of statistical sampling so it
never hurts to get more data, you can always decide to throw some of it out
later. So getting as many interactions as possible makes sense.

~~~
robotmay
Sorry for any oddities in the way the article is written; I haven't posted
anything on a blog in quite a while and I'm a bit rusty :)

More data is definitely needed and I'm open to altering the system once I
understand better how it's working; this is very much an initial stab at
improving the situation!

------
snorkel
Bad headline given the use case which not a currency issue but rather how to
feature quality content that is not as popular:

* Discovery: Good but unpopular content is being buried by popular content

* The noise makers are the taste makers: What is popular is being decided by the most active users

* Popular begets more popular: Rankings that are based on popularity only reinforces the popularity of top-ranked items.

Some communities may decide that this is not a problem and therefore ranking
content by Likes works as is.

However if you want to address those issues, then yes, rationing the available
Likes is one way to approach it. You could also weight the ranking formulas by
percentage of Likes per user (ie. users that have older accounts and give out
less Likes overall are weighted differently)

------
brunosan
Why not just weighting the value of each like by the number of likes given
over a period of time? People who spare the likes will give more value, those
who like it all, won´t really add much value with their like.

~~~
robotmay
This may well be a direction I take it in future once I have more data to make
a more informed decision :)

------
firepoet
Check out: <https://www.centup.org/>

Likes that cause donations to go to your favorite charity!

(I am an acquaintance of one of the founders, but not related in any other
way.)

~~~
robotmay
I like it; it looks kinda like a charitable version of Flattr.

------
jaredsohn
Beyond the various aspects of social utility of "Like" that everyone has
mentioned, a 'Like' can also mean that you want to subscribe to updates from a
source, such as you would do with RSS.

~~~
robotmay
Aye, it does seem to be a very interchangeable term. I use 'Like' in the
article much as you would see on Facebook. I currently have a simplistic
following feature implemented but it's on the roadmap to offer suggestions
based on what you've favourited or recommended in the past too.

------
barce
"Because you can only click ‘Recommend’ 10 times in a day, you can’t go
gallavanting about throwing them hither and thither; they are to be reserved
for the photos which you think other users should see."

This just puts the problem somewhere else.

Now, the new problem is a follower becoming "a flawed" currency. People who
try to bot likes will now bot followers to get more likes.

------
glhaynes
_‘Liking’ your content costs me nothing, so what’s to stop me from ‘Liking’
everything I see without considering how it affects the popularity of that
content?_

Is there evidence that a significant # of users are doing this?

~~~
MartinCron
Even if it is a problem, it's a solvable one. One thing that I did, years ago,
when trying to create an algorithm for what stuff you would find funny, was to
entirely discard the input from the users with the top n% of favorites/likes.

Basically, we determined that some people were just less discerning than
others.

~~~
sirclueless
There's probably better ways of doing this. Some people probably "Like" a
bunch of things because they are less discerning, others do it because they
are legitimate social leaders in their circles. So you may be able to do more
if you have some way of knowing how many things someone sees and chooses _not_
to like, or how many friends subsequently view based on a "Like" (which I
suspect Facebook already considers when choosing what to show on timelines).

------
jsnk
You won't increase the value of something worthless by applying arbitrary
scarcity.

------
abraininavat
They're called "Likes" because they represent what people like. You are
setting a limit on the number of things people like? Your problem isn't with
the concept of likes, it's that you wish they solved a problem which they
don't solve.

You wish they were "recommendations" instead. But this is already a solved
problem. When I like something enough that I want to recommend it to someone
else, I use email. Or I call. Or I mention it in the hallway. Or I comment
about it on Google+.

This type of recommendation existed long before we were born. It doesn't
really need any help from you, but if you want to add a "recommendation"
feature, go for it. But this concept doesn't replace the _completely
different_ concept you might call "like-based recommendations". This is a new
concept that wasn't possible before, and now you're talking about crippling it
by setting artificial limits!

~~~
potatolicious
So don't call it a "like". Call it something else, say "props" or "kudos".

The whole point here is to establish a currency for acknowledging quality, it
need not represent actual "liking" of anything.

There is a deeper point here which is: what is a like anyways? Clicking a
button to indicate you enjoy something has no use for the user. On Facebook
users do it as a form of social signaling. On some other sites "liking" is
essentially bookmarking for later use.

It's important to separate the _actual_ utility of clicking a button vs. the
concept notion of liking something.

> _"You wish they were "recommendations" instead. But this is already a solved
> problem."_

You're conflating two things. What you're talking about is _sharing_ \- you
share a restaurant with a friend, or you share a funny cat picture with your
cousin. "Recommendation" in this context means generating, programmatically,
relevant things for you to look at. The power of "likes" (or any kind of
quality score, really) is that you don't _need_ to know the user's social
graph to locate for them content they will be interested in. Even in a social
networking context, a quality score allows you to expose the user to good
content outside of their immediate social sphere, which on a photography
website is certainly a desired feature.

The website in question is not about viewing the photo feeds of your internet
friends, but about discovering the best content across the _entire_ community,
even from users who are completely disconnected from you in the social graph.

Unless I'm reading this blog post horribly wrong, when you click on
"Recommend" you don't direct this recommendation towards anyone at all. It's
simply "I mark this with my stamp of approval, which in turn will help surface
this good content to other users of this website". There is not a social angle
to this at all, nor any sort of directed sharing.

Anyways, I think this is a great idea. There was a website I used a long time
ago called thesixtyone. It was an indie music site where discoverability was
the core feature. You got "hearts" which you can give to specific songs. Your
hearts replenish daily (use them or lose them), making them a currency, and
preventing you from just heart'ing everything willy-nilly.

There's an elegance to this system that photographer.io can borrow: if you
heart something (and therefore expose it to more users) and they in turn also
heart the song, _you get more hearts to spend_. Essentially, users with taste
that the community agrees with will get a louder voice, and the community
becomes more directed as a result. It also allows you very clear visibility
into influencers in the community.

There was also a neat gamification angle to it that gave achievements for
tasks, with the overall goal of making sure you spend your hearts instead of
doing nothing with them.

~~~
robotmay
> Unless I'm reading this blog post horribly wrong, when you click on
> "Recommend" you don't direct this recommendation towards anyone at all. It's
> simply "I mark this with my stamp of approval, which in turn will help
> surface this good content to other users of this website". There is not a
> social angle to this at all, nor any sort of directed sharing.

You're not wrong - that's exactly how it works! I must apologise for the post
being quite unclear; it has been quite a while since I wrote anything :)

Discoverability is very much one of the core concerns for me, as I feel it's
lacking elsewhere. I like the idea of rewarding people that others agree with,
as that could help encourage users to recommend more often whilst also making
exploitation of the system more tricky.

This is still very much in its early stages and I'm keen to improve on it.
Thanks for the great feedback!

