EdgeRank – Data Science, Data Analytics and Machine Learning Consulting in Koblenz Germany https://www.rene-pickhardt.de Extract knowledge from your data and be ahead of your competition Tue, 17 Jul 2018 12:12:43 +0000 en-US hourly 1 https://wordpress.org/?v=4.9.6 Stop Facebook – Filterbubble of facebook's news stream & wall https://www.rene-pickhardt.de/stop-facebook-filterbubble-of-facebooks-news-stream-wall/ https://www.rene-pickhardt.de/stop-facebook-filterbubble-of-facebooks-news-stream-wall/#respond Tue, 07 Jun 2011 21:31:39 +0000 http://www.rene-pickhardt.de/?p=412 As everyone knows in my limited freetime I am currently doing two tings:

  1. I am reading Eli Parisers book about the filterbubble. I don’t want to review it until I am done which happens hopefully somewhen soon. But it has a connection to the other thing I am doing
  2. I am promoting my Band’s first album ballads n bullets that just came out

I was able to convince my band that money invested in Google Adwords and Facebook is probably a better deal than spending money in print campaigns. Online is much more efficiant to reach our target group and introduce them to our music. So far so good! But sometimes you discover the worst or boldest things while doing something.

Some Background

As we all know facebook is filtering your social newsstream. Recently we did an update and send a reminder to all our fans on facebook (2000) and reminded them about the upcoming release. We got 2500 Impressions and received 100 clicks resulting in 6 sales. Not so cool!
Right now – just by my experience of watching impressions in facebook and several websites und seeing how much traffic comes from facebook to our homepage I am about to belief that Facebook counts ten impressions to your status update if one user visits his facebook news stream 10 times and was therby ten times able to see your news update.
Apperantly it seems that I am not mistaking with my guess. Have a look at Tim Wilson’s post on how Impressions are counted on Facebook:
http://www.gilliganondata.com/index.php/2010/01/27/facebook-measurement-impressions-from-status-updates/
Let us think again what it means to have 2500 Impressions of a status update. Could it be possible that these 2500 impressions have been generated only by a couple of users – let us say less than 200?

See how bold facebook is!

While booking ads facebook is offering me a deal that made me sit down and look twice! I am now able to buy visibility of my own status updates in the social news stream. If I pay for each click my status update receives Facebook will not only show the update to all of our fans. But they will also show the highly filtered interactions of them to their friends!
To make buying advertising even more attractive Facebook is telling me that our friend of a friend network has about 206’000 users that could be reached with the status updates of my band. Up till today my status updates only reached a visibility of 5500 impressions. The 206’000 that facebook offers me is only 40 times as much. Assuming that every user produces only one impression and we know that a user produces many more impressions.
A factor of 40 or higher is an amazingly huge number. Probably the number every marketing person has in mind when he decides that everyone has to be on facebook now!
Isn’t that insane! Facebooks user experience suggests us to be there because we get think that we get this incredible high reach. but the reality is that we get nothing but our premium customers if we don’t pay facebook. Facebook should pay me that I produce such a great content on facebook!

What should I say? It is a curse!

Everyone jumps on the facebook train with the totally wrong expectations. No not everyone and all of their friends see your advertising and status updates!
Of course if something really sepcial happens facebook really makes you viral but most the time you have no advanage by using facebook in comparison to other marketing methods. Especially the only one that is winning always is facebook. I have hardly seen any brand in the world that was printed and promoted on so many flyer / poster / and mags and even tv commercials. Amazingly facebook did not even pay one Cent to appear on all these media. Everyone pushes their own facebook channel – hoping to become viral – instead of pushing their own brand and thinking about how to really bring out the brand and do marketing or thinking about how to make a great product.

Everyone seems to expect miracles from Facebook

Hello everybody! Think about it! The world wide GNP won’t grow just because everyone is now using facebook! It is only facebook that is growing!
By the way I was warning everyone about the fact that you should focus on your website and not on facebook in one of my articles about the perfect band website. It is just to risky to relay on facebook. First it was great. now it is big and policies are changed over and over again!

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Social news streams – a possible PhD research topic? https://www.rene-pickhardt.de/social-news-streams-a-possible-phd-research-topic/ https://www.rene-pickhardt.de/social-news-streams-a-possible-phd-research-topic/#comments Mon, 25 Apr 2011 22:03:08 +0000 http://www.rene-pickhardt.de/?p=351 It is two months now of reading papers since I started my PhD program. Enough time to think about possible research topics. I am more and more interested in search, social networks in general and social news streams in particular. It is obvious that it is becoming more and more important to aggregate news around a users interests and social circle and display them to the user in an efficient manner. Facebook and Twitter are doing this in an obvious way but also Google, Google News and a lot of other sites have similar products.

To much information in one’s social environment

In order to create a news stream there is the possibility to just show the most recent information to the user (as Twitter is doing it). Due to the huge amount of information created, one wants to filter the results in order to gain a higher user experience. Facebook first started to filter the news stream on their site which lead to the widely spread discussion about their ironically called EdgeRank algorithm. Many users seem to be unhappy with the user experience of Facebook’s Top News.
Also for some information such as the existence of an event in future it might not be the best moment to display the information as soon as it becomes available.

Interesting research hook points and difficulties

I observed these trends and realized that this problem can be seen as a special case of search or more general recommendation engines in information retrieval. We want to obtain the most relevant information updates around a certain time window for every specific user.
This problem seems to me algorithmically much harder than web search where the results don’t have this time component and for a long time also haven’t been personalized to the user’s interest. The time component makes it hard to decide the question for relevance. The information is new and you don’t have any votes or indicators of relevance. Consider a news source or person in someone’s environment that wasn’t important before. All of a sudden this person could provide a highly relevant and useful information to the user.

My goal and roadmap

Fortunately in the past I have created metalcon.de together with several friends. Metalcon is a social network for heavy metal fans. On metalcon users can access information (cd releases, upcoming concerts, discussions, news, reviews,…) about their favorite music bands, concerts and venues in their region and updates from their friends. These information can perfectly be displayed in a social news stream. On the other hand metalcon users share information about their taste of music, the venues they go to and the people they are friend with.
This means that I have a perfect sandbox to develop and test (with real users) some smart social news algorithms that are supposed to aggregate and filter the most relevant news to our users based on their interests.
Furthermore regional information and information about music are available as linked open data. So the news stream can easily be enriched with semantic components.
Since I am about to redesign (a lot of work) metalcon for the purpose of research and I am about to go into this direction for my PhD thesis I would be very happy to receive some feedback and thoughts about my suggestions of my future research topic. You can leave a comment or contact me.
Thanks you!

Current Achievments:

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Facebook User Search: Ever wondered how Facebook is more social than others? https://www.rene-pickhardt.de/facebook-user-search-ever-wondered-how-facebook-is-more-social-than-others/ https://www.rene-pickhardt.de/facebook-user-search-ever-wondered-how-facebook-is-more-social-than-others/#comments Mon, 14 Mar 2011 21:58:03 +0000 http://www.rene-pickhardt.de/?p=299 After Eli’s talk on TED and my recent article about the filter bubble I decided to dig a little deeper into Facebook’s EdgeRank algorithm, which decides what Updates appear in your news feed. I found some more scientific background on how EdgeRank really works. Even though EdgeRank was first mentioned on Facebook F8 Live on April 21st in 2010 it is already mentioned in a footnote of the scientific paper “All friends are not equal: using weights in social graphs to improve search” by Sudheendra Hangal, Diana MacLean, Monica S. Lam and Jeffrey Heer all from Computer Science department at Stanford university.
Inspired by this paper I run a little test to compare user Search of Facebook and once (a long time ago) Germanys biggest social networrk StudiVZ. Not surprisingly Facebook clearly won the battle. But let me first give a brief overview on how social networks rose in Germany.

History of Facebook and StudiVZ

So in Germany we there was this Facebook clone – let’s call it StudiVZ – starting in late 2005. Due to the fact that hardly anyone knew of Facebook and StudiVZ started some great word of mouth marketing (and stole the entire design from Facebook) it spread very quickly and became THE social network in Germany. In 2007 / 2008 no one would have imagined how the most popular German Website could ever fall back. StudiVZ (being aquired by a traditional media company) tried to make advertising dollars. While Facebook started to gain real social network know how. Not surprisingly Facebook passed by StudiVZ within a couple of months while 2010.

The Experiment: How good is the user search on social networks?

A must have feature of every social networking site is the user search. So I wanted to test how good does the user search on both sites work. (already knowing that Facebook would easily win this battle) I thought of a person with a very common name that is not a friend of mine on ether of these social networking sites.
After a little bit of thinking I came to Sebastian Jung. On Facebook as well as on StudiVZ he is registered with his real Name. (along with about 140 other Sebastian Jungs in Germany) Sebstian was in my grade in high school together with 130 other students. I hardly know him.

Search for Sebastian Jung on StudiVZ:

Typing his name in StudiVZ brings up his profile to the 4th position. Lucky me that he has recently updated his StudiVZ profile which is to my knowledge the variable the user search results are sorted by. If he hadn’t done this he would have disappeared somewhere between those 140 other Sebstian Jung’s that have a StudiVZ profile with the same name.

Search for Sebstian Jung on Facebook:

Typing his name into Facebook search immidiately shows his profile on the first position. In my case this is particular interesting but let us first explore why Facebook does so well.

How does Facebook user search rank the results?

Of course the exact algorithm is secrete but the idea is easy. As everyone knows we can measure the distance between to people in a social network by the shortest path of people between those two people. Uff. Shortest path?!? What does this mean?
For Sebastian Jung and me this shortest path would be of length 1 since I have some friend from my old school that is a friend of Sebastian Jung. Which in turn means there is one person between Sebastian Jung an me.
For our German Chancellor and me the distance would probably be 3 (wild guess) but I think you get the point. So what facebook does is to sort all the Sebastian Jungs on the result Page according to their distance from me. Pretty smart isn’t it? But Facebook is probably even using a little bit more information. Let us assume I have 4 common friends with this Sebastian Jung and maybe 1 common friend with another Sebastian Jung. The distance in both cases would be 1. But the one I have more common friends with is still probably more relevant to me and will most probably be shown first.

Oh and why is this particular interesting for my case?

You can call me paranoid or something but I am still afraid that facebook knows to much about me if I tell them more about my friendships. That’s why I decided to have 0 friends on Facebook. Obviously Facebook is not only using actual friendships that exist but also the 120 friendshiprequests I have received so far and other knowledge (maybe people have uploaded my email address together with their address book) Anyway this experiment show that my fear obviously has a reason but it also shows that I clearly failed to protect my most sensitive data from Facebook.

Conclusion:

  1. Still I am very convinced that Facebook’s success is due to the fact that these little things just silently work perfect in the background producing great user satisfaction.
  2. As I always say. You cannot steal an idea on the Internet. If you don’t understand the Idea you might have a short success but then you’ll fail because your product will just not be as good as your competitors product
  3. If you want to be successful on the Internet don’t focus on selling ads and making money in the first place. Look what the big players have been doing! Focus on user satisfaction. If your users are happy I am pretty sure the money and reward will come to you!
  4. Even though the pages look a like and StudiVZ is still copying features from Facebook they oviously don’t understand the essence of these features and what exactly makes them great. Otherwise after 5 years of operations they would be able to have a good running user search which should be the kernel of any social networking service.
  5. Much to learn and improve for my own social network Metalcon that has a crappy search function over all (-:
  6. 6. I still haven’t digged deeper into the EdgeRank Algorithm 🙁

I am happy to read about your comments and thoughts as well as your experiments to user search with Facebook and other social networks. What other (technical (!)) reasons do you think make Facebook the superior social network in comparison to sites like myspace, orkut, studiVZ, bebo,… ?

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Algorithmic Information Filter from Eli Pariser’s TED Talks https://www.rene-pickhardt.de/algorithmic-information-filter-from-elis-parisers-ted-talks/ https://www.rene-pickhardt.de/algorithmic-information-filter-from-elis-parisers-ted-talks/#comments Sun, 13 Mar 2011 13:34:06 +0000 http://www.rene-pickhardt.de/?p=285 Just today an interesting story came up on a German news site which goes back to Eli Pariser’s (Homepage, follow @Twitter ) talk on TED about a thing he calls the Filter Bubble and how personalization is changing the Internet. Before commenting on his talk I want to personally thank him to use his reputation and start a discussion on such a fundamental and important topic!
UPDATE most likely you are looking for my list of almost 57 signals google might use to filter
I had a short Mail conversation with Eli. He asked me to temporarly remove his TED talk since his book isn’t on sale yet. I found a very similar talk by him which he allowed me to make public in my blog. So here you go folks:

Google is filtering and personalizing search results

Eli is pointing out a thing some people might have already noticed. If two different people search for the same thing on Google it is very probable that the search results will be very different. Google is doing this without telling the user that it is acutally filtering the results based on what the algorithm thinks the user might like. According to Eli Pariser Google is using 57 signals to determine the interest of us. Among those we find:

Of course this kind of personalization has its good sides. When I am about to buy a new notebook computer y I definitely want to see different Websites if I live in Germany or in the US. This could be due to tax and shipping fees. Which means that I am most probably interested in local stores and not in oversea shops. Still this personalization and filtering is a huge potential for serious problems. Let me ask a few questions:

  • What happens if Google misinterprets our 57 signals?
  • What happens if I only receive results from a certain type?
  • What if I rely to the fact that I have access to all kind of information?

We might think we get all the information we need. But in reality we are becoming blinded by the filters Google is using. We have no chance to determine what other information is filtert and potentially available for a certain topic. On the other hand due to the amount of information we need filters and computers to help us. But the systems should be more transparent!

Facebook is also filtering the newsstream from your friends:

I have always been thinking Facebook’s huge success is strongly correlated to the fact that there is hardly Spam on Facebook and the information economy is very smart and user friendly. The attention of users to status updates is very high making facebook a great place for every company to do online and viral marketing. This of course contributes to Facebook’s reach. In fact the information architecture on Facebook is even so smart that your 20’000 followers on Facebook might not receive your status updates since Facebook’s EdgeRank algorithm decides it is not relevant to your fans or friends. Edgerank might not have 57 signals but it still takes into consideration:

  • who your fans are friend with
  • what other news they like
  • how heavy they have interacted with you in the past
  • the time passed since your last status update

Great news isn’t it? Just compare this with my statement in a recent blog post about creating newsletters as a musician in order to communicate with your fans and not solely rely on other services like Facebook or MySpace.
You don’t believe the Facebook thing? There is a video about the EdgeRank algorithm used by Facebook to determine which status updates should reach us and which shouldn’t. Feel free to have a look and thanks to the guys from Klurig Analytics for producing such a great video resource:

So what can we do?

  1. We should join the discussion in order to pursue Google, Facebook and others to become more transparent.
  2. We should be aware of the fact that a lot of information might not reach us.
  3. Even though more and more information is made available through the Internet we should not become lazy and rely on all these great web services.
  4. Last but not least you can help to spread the information about this topic! As we have seen only if a lot of people spread the information it breaks through the filtering system. And this topic is worth to be spread!

Again thanks a lot to Eli Pariser to start this discussion!

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