FriendFeed “Likes” Compatibility Index Pre-Pre-Pre Alpha

Hutch Carpenter had post about what he called the “Friendfeed Likeability Index”, calculated them for a tiny sample of his own likes, and found them pretty good convincing…

And ofcourse a totally hot conversation started off on Friendfeed about this (interestingly, not only on Hutch Carpenter’s original post, but on one that Louis Gray shared).

Now, Friendfeed has a totally hawt bug that prevents any serious data collection (I discovered this to my dismay after building a backend to Friendfeed for my Stats app), so I can analyse only the last 300 likes. Still, there was enough support for it, so I went ahead and built it.

First Target: LouisGray

Obvious, isn’t it? The ‘face of Friendfeed’?

Here is the list of top 25 people who liked the same stuff LouisGray liked:

Rank	User	Shared-Likes
1	Shey	84
2	Hutch Carpenter	78
3	Atul	61
4	Robert Scoble	51
5	Susan Beebe	49
6	Dobromir Hadzhiev	43
7	Mitchell Tsai	40
8	Julian Baldwin	35
9	Alejandro	34
10	Jason Kineshiro	32
11	Thomas Hawk	30
12	nikpay	29
13	Andrew Dobrow	28
14	RobD iana	27
15	Mark Trapp	25
16	Phil Glockner	25
17	Mike Reynolds	24
18	Edythe	24
19	Morton Fox	23
20	Charlie Anzman	23
21	Anthony Farrior	22
22	Robert Seidman	22
23	Colin Walker	22
24	Bwana McCall	21
25	Tris Hussey	20

I’ve followed some new folks with this – notably, Shey, Atul and Susan Beebe. Certainly helps discover new folks. And, not many “A-List” Celebs here – Excepting a few.

Since Scoble comes in at No.4, rumors of Louis and Scoble marrying so that they can “like” each other in public seem to be totally exaggerated (People who do not frequent friendfeed are expected to get the joke by following this link and reading the 6^th comment by Alexander van Elsas)

Secondary Target: Robert Scoble

Shiny new thing hunter, Friendfeed enthusiast, and ofcourse, wants to be at the top of every single list!

Here’s his list:

Rank	User	Shared Likes
1	Mitchell Tsai	44
2	Atul	32
3	Susan Beebe	28
4	Shey	27
5	Louis Gray	24
6	Nkpay	22
7	Dobromir Hadzhiev	21
8	Anthony Farrior	21
9	Sarah Perez	21
10	Duncan Riley	20
11	Hutch Carpenter	20
12	Robert Seidman	19
13	Phil Glockner	18
14	Edythe	16
15	Mark Trapp	15
16	Charlie Anzman	14
17	Tris Hussey	14
18	Sally Church	14
19	Micheal Beck	14
20	Paula Hawk	13
21	Baard Overgaard Hansen	12
22	Eric Florenzano	11
23	Timothy Neilen	11
24	Paris Lemon	11
25	CJ Cloote	11
26	Brian D. Eisenberg	11

Note that Scoble is way less similar to other people than Louis Gray – Louis Gray and Shey had 84 likes shared between them, while Scoble and Mitchell Tsai have only 44 between them. I’m not really too sure about how to interpret this (Both have same sample size, last 300 likes). Conducted some additional tests and I now know – Scoble spread out his last 300 likes to 202 users, while Louis spread his out to only 118 users. So, from this sample, it appears that Scoble is actually exploring more people than Louis Gray does. Interesting.

Note that this stuff is pretty non-representative, since the sample is only the last 300 likes from Louis and Scoble. Once FriendFeed fixes that bug, then the “real” analysis will be able to give us more insight. Maybe, more people shouting for that bug to be removed will get that bug to be removed? (wink, wink)

Want to see your “Friendfeed Likes Compatibility Index”? Comment here and I’ll post it as immediately as possible (Am not releasing the .NET Script I wrote since it’s too hacky. Still, if enough people are interested, I’ll clean it up and put it up somewhere)

This entry was posted on Thursday, May 29th, 2008 at 11:21 am and is filed under Friendfeed. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.

Viewing 13 Comments

cynabhathena 1 month ago 1 point
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I like these lists that you make based on statistical data. I mean who ends up making lists on the basis of the number of people who liked or disliked a particular post! Anyway, its always different and interesting. Though I'm not particularly agreeing to your thought that when people 'like' something, they're really interested in the content.
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1 /people/cynabhathena/ /people/cynabhathena/following/

millipo37 2 months ago 1 point
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Did you hear about the fellow that was talking to his buddy, when he said, "I don't know what to get my wife for her birthday. She has everything, and besides, she can afford to buy anything she wants. So, I'm stumped."

His buddy said, "I have an idea. Why don't you make up a certificate that says she can have two hours of great sex, any way she wants it. She'll probably be thrilled!" So the first fella did just that.

The next day his buddy asked, "Well, did you take my suggestion? How did it turn out?"

"She loved it. She jumped up, thanked me, kissed me on the mouth, and ran out the door yelling, 'I'll see you in two hours'."

respect
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apple store locations 2 months ago 1 point
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Good stuff,really liking the way how it works.Could not have work better than that.The lists that yr making,it is pretty convincing to me.Thanks for the great work!

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http://applestorelocations.net/

STD Symptoms 3 months ago 1 point
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Thanks for sharing such nice post. Its so useful.

Regards

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1 /people/summad98/ /people/summad98/following/ http://www.checkstdsymptoms.com/

bridal shower ideas 3 months ago 1 point
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My major problem with the “Likes” is that judging from our blog’s stats like does not actually mean that you are really-really interested in the content. For example, for a post with over 30 likes only 20 people actually clicked through to see the post itself. To me it means that people only click “Like” to ensure their presence on FF, not to actually join the conversation or show their real interests. Pretty hard to graph something on such type of information, no?

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http://bridalshoweretc.com/

Cheap Xbox 360 3 months ago 1 point
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Great post, get a lot information about Friendfeed, thanks for the great work!

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1 /people/CheapXbox360/ /people/CheapXbox360/following/ http://www.cheapxbox360.org/

Car hire insurance 3 months ago 1 point
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Insights like this are invaluable - nice work with the .NET script. Data visualisations like this are the future - especially for the social web. Top work.

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DVD Boxset 3 months ago 1 point
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Good stuff,really liking the way how it works.Could not have work better than that.The lists that yr making,it is pretty convincing to me.Thanks for the great work!

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1 /people/dvdboxset/ /people/dvdboxset/following/ http://www.collectiondvdboxset.com

DVD Boxset 3 months ago 1 point
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Good stuff,really liking the way how it works.Could not have work better than that.The lists that yr making,it is pretty convincing to me.Thanks for the great work!

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1 /people/dvdboxset/ /people/dvdboxset/following/ http://www.collectiondvdboxset.com

Best Car Insurance 3 months ago 1 point
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Thanks for sharing

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1 /people/blacksirius/ /people/blacksirius/following/ http://www.bestcarinsurance2u.com/

Frank Polenose 3 months ago 1 point
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Good stuff - like the way this works.
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2 /people/frankpolenose/ /people/frankpolenose/following/ http://www.todayloan.co.uk

cheap logo design 4 months ago 1 point
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able to give us more insight. Maybe, more people shouting for that bug to be removed will get that bug to be removed?

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Cheap Auto Insurance Quotes 4 months ago 1 point
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love these lists that you make :)

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7 /people/cheapautoinsurancequotes/ http://www.4insure.net