Of course this setting is only half realistic:

• Every policeman would have to have a smartphone and use it during work time
• Every policeman would have to install the app of the criminal
• The criminal can distinguish between policemen and other people using the app (should be possible with data mining)
• The criminal can decide weather the policeman is currently working or in leisure time

But it should show and demonstrate the dangers…

To conclude:

We have to disallow policemen to use private smart phones during work! Or if they do so they must not install any applications from a source they don’t trust. And here is the crucial point. Who to trust and who not? Trust usually is created through social ties. So if the app is there and some policemen like the service and recommend it to their coworkers trust is created. Who does really ask about the source of an app and about who is running/owning the data servers. A service that is well known on the web can easily run by 2 or 3 people and even if they are nice it is easy to manipulate or blackmail them in order to get access to these very sensitive data.
And on another more technical topic: We need a decentralized mobile space. There has to be a frequency on which people are able to set up their own transmitters and create decentralized mobile networks. It is a shame that those frequencies are all owned by companies creating centralized services.
By the way this would be a good solution since it would also enable the police to have their own decentralized mobile networks giving them privacy against third parties!

Disclaimer:

I never thought I would write an article in this paranoid way telling people what is possible and where the risks are. I almost feel like a member of ccc, anonymous or finally like a real pirate. But one year of PhD in a very data driven environment having social networks, information retrieval and the web as a focus really makes me understand more and more what is possible (in particular easy to achieve). Also the low awareness of society about these dangers (probably due to the complex technologies) overwhelms me and makes me feel like I have to act and at least inform people.
To bad that mostly people who are already aware of these topics read my blog. Maybe I have to go geek and create this app to demonstrate the functionality in order to really rise awareness. There are just too many interesting things to do during a PhD program so I think this time only writing about this has to be sufficient.

Beginning of our Product Requirement Document

We propose to create a new website for the scientific community which brings together people which are reading the same paper. The basic idea is to mix the functionality of a Q&A platform (like MathOverflow) with a paper database (like arXiv). We follow a strict openness principal by making available the source code and the data we collect.
We start with an analysis how the internet is currently used in different fields and explain the shortcomings. The actual product description can be found under the section “Basic idea”. At the end we present an overview over the websites which follow a similar approach.
This document – as well as the whole project – is work in progress. We are happy about any kind of comments or other contributions.

The distribution of scientific knowledge

Every scientist hast to stay up to date with the developments in his area of research. The basic sources for finding new information are:

• Conferences
• Research Seminars
• Journals
• Preprint-servers (arXiv)
• Review Databases (MathSciNet, Zentralblatt, …)
• Q&A Sites (MathOverflow, StackOverflow, …)
• Blogs
• Social Networks (Twitter, Google+)
• Bibliograhpic Databases (Mendeley, nNode, Medline, etc. )

Every community has found its very own way of how to use this tools.

Mathematics by Heinrich Hartmann – Oxford:

To stay up to date with recent developments I check arxiv.org on a daily basis (RSS feed) participate in mathoverflow.net and search for papers over Google Scholar or MathSciNet. Occasionally interesting work is shared by people in my Google+ circles. In general the speed of pure mathematics is very slow. New research often builds upon work which has been out for a few years. To stay reasonably up to date it is enough to go to conferences every 3-5 months.
I read many papers on myself because I am the only one at the department who does research on that particular topic. We have a reading class where we read papers/lecture notes which are relevant for more people. Usually they are concerned with introductions to certain kinds of theory. We have weekly seminars where people talk about their recently published work. There are some very active blogs by famous mathematicians, but in my area blogs play virtually no role.

Computer Science by René Pickhardt – Uni Koblenz

In Computer Science topics are evolving but also changing very quickly. It is always important to have both an overview of upcoming technologies (which you get from tech blogs) as well as access to current research trends.
Since the speed in computer science is so fast and the review process in Journals often takes much time our main source of information and papers are conferences and twitter.

• Usually conference papers are distributed digitally to participants. If one is interested in those papers google queries like “conference name year papers” are frequently used. Sites like http://www.sciweavers.org/ host and aggregate preprints of papers and organize them by conference.
• The general method to follow a conference that one is not attending is to follow the hashtag of the conference on Twitter. In general Twitter is the most used tool to share distribute and find information not only for papers but also for the above mentioned news about upcoming technologies.

Another rich source for computer scientists is, of course, the related work of papers and google scholar. Especially useful is the method of finding a very influential paper with more than 1000 citations and find newer papers that quote this paper containing a certain keyword which is one of the features of google scholar.
The main problem in computer science is not to find a rare paper or idea but rather to filter the huge amount of publications and also bad publications and also keep track of trends. In this way a system that ranks and summarize papers (not only by abstract and citation counts) would help me a lot to select what related work of a paper I should read!

Psychology by Elisa Scheller – Uni Freiburg

As a psychologist/neuroscientist, I receive recommendations for scientific papers via google scholar alerts or science direct alerts (http://www.sciencedirect.com/); I receive alerts regarding keywords or regarding entire journal issues. When I search for a certain publication, I use pubmed.org or scholar.google.com. This can sometimes be kind of annoying, as I receive multiple alerts from different sources; but I guess it is the best way to stay up to date regarding recent developments. This is especially important in my field, as we feel a big amount of “publication pressure”; I work on a method which is considered as “quite fancy” at the moment, so I also use the alerts to make sure nobody has published “my” experiment yet.
Sometimes a facebook friend recommends a certain publication or a colleague points me to it. Most of the time, I read articles on my own, as I am the only person working on this specific topic at my institution. Additionally, we have a weekly journal club where everyone in turn presents work which is related to our focus of research, e.g. a certain part of the human brain. There is also a weekly seminar dedicated to presentations about ongoing projects.
Blogs (e.g. mindhacks.com, http://neuroskeptic.blogspot.com/) can be a source to get an overview about recent developments, but I have to admit I use them mainly for work-related entertainment.
All in all, it is easy to stay up to date using alerts from different platforms;  the annoying part of it is the flood of emails you receive and that you are quite often alerted to articles that don’t fit your interests (no matter how exact you try to specify your keywords).

Biomedical Research by Johanna Goldmann – MIT

In the biological sciences, in research at the bench – communication is one of the most fundamental tools a scientist can have. Communication with other scientist may open up the possibilities of new collaborations, can lead to a completely new view point of a known question, the integration and expansion of methods as well as allowing a scientist to have a good understanding of what is known, what is not known and what other people have – both successfully and unsuccessfully – tried to investigate.
Yet communication is something that is currently very much lacking in academic science – lacking to the extent that most scientist will agree hinders the progress of research. Nonetheless the lack of communication and the issues it brings with it is something that most scientists will have accepted as a necessary evil – not knowing how to possibly change it.
Progress is only reported in peer-reviewed journals – many which are greatly affected not only but what is currently “sexy” in research but also by politics and connections and the “publish or perish” pressure. Due to the amount of this pressure in publishing in journals and the amount of weight the list of your publications will have upon any young scientists chances of success, scientist tend also to be very reluctant in sharing any information pre-publication.
Furthermore one of the major issues is that currently there really is no way of publishing or communicating either negative results or minor findings, which causes may questions or methods to be repeatedly investigated as well as a loss of information.
Given how much social networks and the internet has changed communication as well as the access to information over the past years – there is a need for this change to affect research and communication in the life science and transform the way we think not only about solving and approaching research questions we gather but the information and insights we gain as a whole.

Philosophy by Sascha Benjamin Fink – Uni Osnabrück

The most important source of information for philosophers is http://philpapers.org/. You can follow trends going on in your field of interest. Philpapers has a list of almost all papers together with their abstracts, keywords and categories as well as a link to the publisher. Additional information about similar papers is displayed.
Every category of papers is managed by some editor. For each category it is possible to subscribe to a newsletter. In this way once per month I will be informed about current publications in journals related to my topic of interest. Every User is able to create an account and manage his literature and the papers of his he is interested in.
Other research and information exchange methods among philosophers consist of mailing lists, reading clubs and Blogs. Have a look at David Chalmers blog list. Blogs are also becoming more and more important. Unfortunately they are usually on general topics and discussing developments of the community (e.g. Leiter’s Blog, Chalmers’ Blog and Schwitzgebel’s Blog).
But all together I still think that for me a centralized service like Philpapers is my favourite tool because it aggregates most information. If I don’t hear about it on Philpapers usually it is not that important. I think among Philosophers this platform – though incomplete – seems to be the standard for the next couple of years.

Problems

As a scientist it is crucial to be informed about the current developments in the research area. Abstracting from the reports above we divide the tasks roughly into the following stages.

1. Finding and filtering new publications:

• What is happening right now? What are the current hot topics my area? What are current trends? (→ Check arXiv/Twitter)
• Did a friend of mine write something? Did a “big shot” write something?
  (→ Check meta information: title, authors)
• Are my colleagues excited about a new development? (→ Talk to them.)

2. Getting more information about a given paper:

• What is actually done in a given paper? Is it relevant for me? Is it really new? Is it a breakthrough? (→ Read abstracts. Find a good readable summary/review.)
• Judge the quality of a paper: Is it correct? Is it well written?
  ( → Where is it published, if at all? Skim through content.)

Finally there is a fundamental decision: Shall I read the whole paper, or not? which leads us to the next task.

3. Understanding a paper: Understanding a paper in depth can be a very time consuming and tedious process. The presentation is often very short and much knowledge is assumed from the reader. The notation choices can be bad, so that even the statements are hard to understand. In effect the paper is easily readable only for a very small circle of specialist in the area. If one is not in the lucky situation to belong to that circle, one usually applies the following strategies:

1. Lookup references. This forces you to process a whole tree of older papers which might be hard to read, and hard to get hold of. Sometimes it is worthwhile to consult a textbook to polish up fundamentals.
2. Finding additional resources. Is there a review? Is there a related video lecture or slides explaining the material in more detail? Is the author going to a conference in the near future, or even giving a seminar in the area?
3. Join forces. Find people thinking about the same paper: Has somebody at my department already read the paper, so that I can ask some questions? Is there enough interest to make a reading group, or more formally, run a seminar about that paper.
4. Contact the author. This a last resort. If you have struggled with understanding the paper for a very long time and really need/want to get it, you might eventually write an email to the author – who might respond, or not. Sometimes even errors are found! – and not published! An indeed, there is no easy way to publish “errata” anywhere on the net.

In mathematics most papers are not getting read though the end. One uses strategies 1 & 2 till one gets stuck and moves on to something more exciting. The chances of survival are much better with strategy 3 where one is committed putting a lot of effort in it over weeks.

4. Finding related work. Where to go from there? Is the paper superseded by a more recent development? Which are the relevant papers which the author builds upon? What are the historic influences? What are the founding ideas of the subject? Finding related work is very time consuming. It is easy to overlook things given that the references are often vast, and sometimes hard to get hold of. Getting information over citations requires often access to commercial databases.

Basic idea:

All researchers around the world are faced with the same problems and come up with their individual solutions. There are great synergies in bringing these people together with an online platform! Most of the addressed problems are solved with a paper centric service which allows you to…

• …get to know other readers of the paper.
• …exchange with the other readers: ask questions, write comments, reviews.
• …share the gained insights with the community.
• …ask questions about the paper.
• …discuss the paper.
• …review the paper.

We want to do that with a new mixture of a traditional Q&A system like StackExchange or MathOverflow with a paper database and social features. The key features of this system are as follows:

Openness: We follow a strict openness principle. The software will be developed in open source. All data generated on this site will be under a creative commons license (like Wikipedia) and will be made available to the community in form of database dumps or an API (open data).

We use two different types of content sites in our system: Papers and Discussions.

Paper sites. A paper site is dedicated to a single publication. And has the following features:

1. Paper meta information
   – show title, author, abstract, journal, tags
   – leave a comment
   – write a review (with wiki option)
   – vote up/down
2. Paper resources
   – show pdfs, slides, notes, video lectures, etc.
   – add a resource
3. Related Work
   – show the reference-tree and citations in an intelligent way.
4. Discussions:
   – show related discussions
   – start a new discussion
5. Social features
   – bookmark
   – share on G+, twitter

The point “Related Work” deserves some further explanation. The citation graph offers a great deal more information than just a list of references. Together with the user generated content like votes and the individual paper bookmarks and social graph one has a very interesting data set which can be harvested. We want this point at least view with respect to: Popularity/Topics/Read by Friends. Later on one could add more sophisticated, even graphical views on this graph.

Discussion sites. A discussion looks more like a traditional QA-question, with the difference, that each discussion may have related (many) papers. A discussion site contains:

1. Discussion meta information (title, author, body)
2. Discussion content
3. Related papers
4. Voting
5. Follow/Bookmark

Besides the content sides we want to provide the following features:

News Stream. This is the start page of our website. It will be generated from the network consisting of friends, papers and authors. There should be several modes like:

• hot: heavily discussed papers/discussions
• new papers: list new publications (filtered by tag, like arXiv feed)
• social: What did your friends do lately
• default: intelligent mix of recent activity that is relevant to the logged in user

Moreover, filter by tag should be always available.

Search bar:

• Searches contents of the site, but should also find papers on freely available databases (e.g. arXiv). Adding a paper should be very seamless process from there.
• Search result ranking uses vote and view information.
• Personalized search information. (Physicists usually do not want sociology results.)
• Auto completion on paper titles, author, discussions.

Social: (hard to implement, maybe for second version!)

• Easily refer to users by @-syntax familiar from Twitter/Google+
• Maintain a friendship / trust graph
• Friendship recommendations
• Find friends from Google+ on the site

Benefits

Our proposed websites improves the above mentioned problems in the following ways.
1. Finding and filtering new publications:This step can be improved with even very little  community effort:

• Tell other people, that you are interested in the paper. Vote it up or leave a comment if you are very excited about it.

• Point out a paper to a colleague.

2. Getting more information about a given paper:

• Write a summary or review about a paper you have read or skimmed through. Maybe the introduction is hard to read or some results are not clearly stated.
• Can you recommend reading this paper? Vote it up!
• Ask a colleague for his opinion on the paper. Maybe he can write a summary?

Many reviews of new papers are already written. E.g. MathSciNet and Zentralblatt maintain a large database of Reviews which are provided by the community and are not freely available. Many authors would be much more happy to write them to an open system!
3. Understanding a paper:Here are the mayor synergies which we want to address with our project.

• Ask a question: Why is the author using this experimental method? How does Lemma 3.4 work? Why do I need this assumption? What is the intiution behind the “virtual truncation”? What implications does this work have?
• Start a discussion: (might involve more than one paper.) What is the difference of these two papers? Is there a reference explaining this more clearly? What should I read in advance to understand the theory?
• Add resources. Tell the community about related videos, notes, books etc. which are available on other sites.
• Share your notes. If you have discussed a paper in a reading class or seminar. Collect your notes or opinions and make them available for the community.
• Restate interesting statements. Tell the community when you have found a helpful result which is buried inside the paper. In that way Google may find it!

4. Finding related work. Having a well structured and easily navigable view on related papers simplifies the search a lot. The filtering benefits from the content generated by the users (votes) and individual information, like friends who have written/bookmarked a paper.

Similar Sites on the Web

There are several discussions in QA forum which are discussing precisely this problem:

• Quora.com: Where can I comment on sci papers?
• MathOverflow: Good websites for discussions of mathematical papers?
• MathOverflow: Is a free alternative to MathSciNet possible?
• MathOverflow: Errata-Database

We found three sites on the internet which follow a similar approach which we examined more carefully.
1. There is a social network which has most of our features implemented:

researchgate.net
“Connect with researchers, make your work visible, and stay current.”

The Economist has dedicated an article to them. It is essentially a facebook clone, with special features for scientist.

• Large, fast growing community. 1.4m +50.000/m. Mainly Biology and Medicine.
  (As Daniel Mietchen points out, the size might be misleading due to institutional accounts)
• Very professional Look and Feel. Company from Berlin, Germany, funded by VC. (48 People involved, 10 Jobs advertised)
• Huge Feature set:
• Profile site, Connect to friends
• News Feed
• Publication Database, Conference Finder, Jobmarket
• Every Paper its own page: with
• Voting up/down
• Comments
• Metadata (Title, Author, Abstract, Preveiw)
• Social Media (Share, Bookmark, Follow author)
• Organize Workgroups/Reading Classes.

Differences to our approach:

• Closed Data / Closed Source
• Very complex site which solves a lot of purposes
• Only very basic features on paper site: vote/comment.
• QA system is not linked well to paper database
• No MathML
• Mainly populated by undergraduates

2. Another website which comes reasonably close is:

http://www.sciweavers.org/

“an academic network that aggregates links to research paper preprints
then categorizes them into proceedings.”

• Includes a large collection of online tools for various purposes
• Have a big library of papers/software/datasets/conferences for computer science.
  Paper sites have:
• Meta information and preview
• Vote functionality and view statistics, tags
• Comments
• Related work
• Bookmarking
• Author information
• User profiles (no friendships)

Differences to our approach:

• Focus on computer science community
• Comment and Discussions are well hidden on paper sites
• No News stream
• Very spacious design

 
3. Another very similar site is:

journalfire.com – beta
“Share what your read – connect to colleagues – create journal clubs.”

It has the following features:

• Comment on Papers. Activity feed (?). Follow articles.
• Host Journal Clubs. Create Events related to papers.
• Powerful search box fetching papers from Arxiv and Pubmed (slow)
• Social features on site: User profiles, friend finder (no fb/g+ integration yet)
• News feed – from subscribed papers and friends
• Easy paper import via Bookmarklet
• Good usability!! (but slow loading times)
• Private reading clubs cost money!

They are very skilled: Maintained by 3 PhD students/postdocs from Caltec and MIT.

Differences to our approach:

• Closed Data, Closed Source
• Also this site misses (currently) misses out ranking features
• Very Closed model – Signup required
• Weak Crowd sourcing: Cannot add Meta information

The site is still at its very beginning with little users. The project started in 2010 and did not gain much momentum since.

The other sites are roughly classified in the following categories:
1. Single people who are following a very similar idea:

• annotatr.appspot.com. Combines a metadata-base with the disqus plugin. You can comment but not rate. Good usability. Nice CSS. Good search function. No MathML. No related article suggestion. Maintained by two academics in private time. Hosted on Google Apps. Closed Source – Closed Data.
• r-Forum – a resource where mathematicians can collect record reviews, corrections of a resource (e.g. paper, talk, …). A simple Vanilla-Forum/Wiki with almost no content used by maybe 12 people in US. No automated Data import. No rating system.
• http://math-arch.org/ – Post comments to math papers. very bad usability – get even errors. Maintained by a group of russian programmers LogicSun. Closed Source – Closed Data.

Analysis: Although the principal idea to connect people reading papers is there. The implementation is very bad in terms of usability and even basic programming. Also the voting features are missed out.

2. (Semi) Professional sites.

• Public Libary of Science very professional, huge paper data base for mainly biology, medicine. Features full text papers, lots of interesting meta information including references. Has comment features (not very visible) and news stream on the start page.
  No QA features (+1, Ask question) on the site. Only published articles are on the site.
• Mendeley.com – Huge Bibliographic database with bookmarking and social features. You can organize reading groups in there, with comments and notes shared among the participants. Features a news stream with papers by friends. Nice import. Impressive fulltext data and Reference features.
  No QA features for paper. No comments for paper. Requires Signup to do anything useful.
• papercritic.com – Open review database. Connected to Mendely bibliographic libary. You can post reviews. No rating. No comments. Not open: Mendely is commercial.
• webofknowledge.com. Commercial academic citation index.
• zotero.org – features programm that runs inside a browser. “easy-to-use tool to help you collect, organize, cite, and share your research sources”

Analysis: The goal of all these tools is to simplify the reference management, by providing metadata like references, citations, abstracts, author profiles. Commenting features on the paper site are not there or not promoted.
3. Vaguely related sites which solve different problems:

• citeulike.org – Social bookmarking for papers. Closed Source – Open Data.
• http://www.scholarpedia.org. A peer reviewed open access encyclopedia.
• Philica.com Online Journal which publishes articles from any field along with its reviews.
• MathSciNet/Zentralblatt – Review database for math community. Closed Source – Commercial.
• http://f1000research.com/ – Online Journal with a public, post publish review process. “Open Science – Open Data – Open Review”
• http://altmetrics.org/manifesto/ as an emerging trend from the web-science trust community. Their goal is to revolutionize the review process and create better filters for scientific publications making use of link structures and public discussions. (Might be interesting for us).
• http://meta.wikimedia.org/wiki/WikiScholar – one of several ideas under discussion at Wikimedia as to a central repository for references (that are cited on Wikipedias and other Wikimedia projects)

Upshot of all this:

There is not a single site featuring good Q&A features for papers.

If you like our approach you can contact us or contribute on the source code find some starting documentation!
So the plan is to fork an open source question answer system and enrich it with the features fulfilling the needs of scientists and some social aspects which will eventually help to rank related work of a paper.
Feel free to provide us with feedback and wishes and join our effort!

• Press release: http://wikimediafoundation.org/wiki/Press_releases/English_Wikipedia_to_go_dark
• Letter to Users: http://wikimediafoundation.org/wiki/English_Wikipedia_anti-SOPA_blackout 
• User discussion: http://en.wikipedia.org/wiki/Wikipedia:SOPA_initiative/Action see below for a saved copy!

This is such an important move of democracy that I was standing still for a couple of minutes after I heard of this! 1’800 active wikipedia authors moderators and administrators collectively agreed to make this move in order to show a protest! I am very excited to see where this will be going and what impact this has. Freedom of the internet is what makes this such a beautiful space. Everyone spread this word! discuss this! Don’t let anyone take the freedom of speech and information sharing from you!
Since the user discussion and poll won’t be available tomorrow I attached them to my blogpost.
http://www.rene-pickhardt.de/wp-content/uploads/2012/01/Wikipedia-SOPA-initiative-Action-Wikipedia-the-free-encyclopedia.html
I will not comment on this any further. Please everyone Have your own oppinion and act with responsability.

“I want to fix the health system. I want to fix our education system. I have no idea how to do it. I have half a dozen ideas. We try them out. They will probably all fail. Then we test some other ideas out. Will find some that work. We get rid of those that don’t“

Tim points out that not only he hasn’t met the politician yet but our behaviour is also not like this. He says:

“But more importantly when voters like you an me are willing to vote for that kind of a politian on that platform I will admit that it is obvious that trial and error works…“

The only thing that borders me about this talk is that it had to be an authority like Tim Harfords on an event with a lot of authority like TED to say these words and get heard. Anyway enjoy the following TED talk by Tim Harford

I think trial and error is a very important way to be creative and find smart solutions. I think especially in science as well as R&D a lot of results come from trial and error. Most people just don’t admit it. We should think about our perspective on trial and error and make this behaviour more acceptable within our society.
Tell me what great ideas did you get through trial and error?

Advertising on the rest of the web is still much more profitable than advertising on social networks.

If Facebook continues to attract advertisers, they could easily create an ad program that is similar to Google Adsense. Many Facebook-users provide the network with detailed information about their interests. Thus, Facebook will be able to deliver highly personalized advertising to any user on any website. They don’t even have to care about the websites content. Even if the user would not have a Facebook-account, Facebook could still be able to predict the topics of interest for users of a website and again deliver highly personalized ads that do not necessarily have to correspond to the content of the website. I strongly believe that this is the real thread coming from Facebook to Google and this is what Google is afraid of!
What is your oppinion? Why do you think Google had to enter the social networking market?

All this comes at a very high price.

Since I started blogging and working on my PhD, I also started to use Twitter. So I wanted to download a Twitter app from the Android app market. It is incredible that the official Twitter app asks permission to access my phone’s address book. Remember, my phones address book is just a copy of my Gmail address book. I see how it helps Twitter to increase their service but to me, it became just too easy to share very sensitive data with companies that you might not (?) trust. I wonder whether the service Twitter offers to us will really improve that much if we share our private address book with the company. In my opinion, the small improvement we get does not justify their need to access my private address book. What would I have to promise someone to have a copy of his address book?

Can I escape?

I decided not to install the Twitter app. But does that really make sense? I guess most people don’t mind. After all, it is Twitter, a well known brand, that asks for the data. Additionally, Twitter is a communication service, so it makes sense to share this kind of data. However, even if I don’t share, Twitter can still guess the entries of my address book. Most of my friends who use Twitter with an android phone will probably accept the terms and condition of the Twitter app. Does not installing the app really help to protect my and my friends(!) privacy?
It is amazing that I am thinking right now about the consequences of blogging my experience of interviewing with Google when exactly this company creates structures that make us all sit in a glass house! I am very sure that this is intentionally like this. Please don’t missunderstand me. My first impression of Android is very good and I knew before that it encourages you in several ways to share data with anyone. Still, Android is probably one of the most useful tools which were brought to customers within the last ten years. I am only pointing out that things are changing very fast these days.

Which Android apps do I need?

So far I have:

• Google Maps
• Gmail
• Google Search
• Google Voice Recognition
• Google Reader
• Google News
• Tweetdeck (without sharing my address book !)
• Ankidroid
• Google Docs
• Google Calendar

What else would you suggest? And no, I don’t want a Facebook app. (-:

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!

So here you go with my little open source experience:

About 2 weeks ago I was in the middle of redesigning metalcon. I already had a database schema ready and was discussing it with friends. Jonas gave me a call he suggested to look for a different database software since my schema was much more like a graph. From my PhD advisor I knew that there are some researchers working on a thing called graph data bases. I opened my first choice search engine and typed in graph data base. After a little bit of reading I got to know the open source Graph data base called neo4j. Apperently Neo4j seemed to be the most sophisticated Graph data base that exists so far. Since we want to use it as our core technology of metalcon being sophisticated is quite an important propertie.
Anyway I downloaded the database and did some first testings of neo4j’s speed. I was amazed. I was also amazed that in comparison to some other graph databases this strong and powerfull tool is available for free. I could not afford to spend money right now so I decided I want to return something to the open source community of neo4j and contribute to the project.But what could it be?

1. I had some trouble in setting it up together with google web toolkit and I didn’t find any resources on the web (due to the fact that neo4j isn’t to famous yet and the resources just did’t exist). Usually I wouldn’t care. After getting a piece of software working I would be happy and start using it. But neo4j as a startup is open source. The people who are driving the project have the right scope. So I realized that making a screencast on neo4j with gwt would be my way to contribute to the open source project.
2. After i did that the guys from neo4j contacted me and asked me for feedback on their documentation. So I read the documentation again and wrote down every question I had. not to ask them to answer the questions but to show them what is unclear to a reader. Again the guys from neo4j have been very happy.

A screencast and “proofreading” of course is nothing in comparison to programming a whole database management system but it helps others to quicker leran neo4j which mght result in more customers. Especially the guys from neo4j don’t need to do it and can focus on improving their software. So open source wins. They would not have earned a single dollar on me if it had a commercial licence. But they would have had less publicity and at least also one friend less.
Do you see what I mean? Do you see why open source wins in a world where everyone is connected and information can be distributed very quickly?