buddies and business

L'épicerie in Lyon

The more I get into relation detection via communication data, the more services come to my mind. But of course, I don’t invent this wheel for the first time (Pete Warden’s blog brought a lot of evidence to me): In an article two years from now (already!) ZDnet UK has a nice portrait about the emerging business of email analysis. A positive focus is put on Clearwell Systems because of their special (unique?) ranking algorithm (oha! — I bet Google pays very close attention). Its software

weighs the background data and content of each email for several factors, including the name of the sender, names of recipients, how many replies the message generated, who replied, how quickly replies came, how many times it was forwarded, attachments and, of course, keywords.

Well, so do I… But in the light of a fully grown business, ranking emails gets away from a personal (autonomous) assistant that is just nice to have, handy and good for reflection. With the huge amounts of email produced every day and about every topic relevant to any business process, corporate email archives contain pretty any information a manager, and — more delicately — a prosecutor can desire:

Email has come to be viewed as a source of truth. If you want to know what really happened, you look at the email.

As it became clear to me, too, during my research, collecting and archiving (intercepting?) all electronic conversations improves the the basis for statistical analysis and heuristics and hence the quality of the ranking a lot. A lot of entities (Google, security authorities) are after our data, consequentially.

Pete Warden has to receive an honrable mention once more because his position of “trying to generate a useful index with no human intervention” resonates with my basic motivation, too. I find his blog to be imensly interesting and very relevant for my thesis: Like expoiting the time information inherent to email that I thought of using in some kind of “contact profiling”, all the privacy issues entangled, especially in business context, and drawing profit from the knowledge that accumulates often unnoticed in a company (or workgroup). And he complains about the missing Gmail Api, too. All written in a very comprehensive manner.

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User Testing

paper prototype

interacting with paper prototype

sketches after testing session

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How to pick friends

myfolks selector

Imagine, you’re back from a trip abroad and want to tell your friends about all the fascinating experiences that you have made (And you either don’t have a blog for that purpose or don’t want to publish it publicly). Usually, that means you have to go through your entire address book and select the appropriate persons. However, if your computer knew about your relationships it could help you a lot with this task.

How could an interface for this case look like? Here are some propositions (and some problems to discuss!).

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Autonomous Assistants reloaded

Here comes the all new and sparkling abstract of my Thesis (old stuff). You might want to have a look at it and give it some comments!

In my thesis I propose the idea of a socially aware computer. In order to get to know the user‘s circles of friends, it will mine and analyse the data that is left as traces by her communication, mainly phone call logs and email archives. As a result, a value for personal or subjective importance can be computed for each person in the user‘s network.

This allows for a new arrangement of the personal address book so that more relevant persons can be found more easily – an important feature regarding our ever expanding and globalized personal networks.
Moreover, tasks that require knowledge about the user‘s personal relations can be handled automatically: One is turning the user‘s attention towards old friends that tend to be neglected when he is burried in work or because he is always on the run due to our mobile and flexible times. Another one is managing access to her personal data that she stores online, like photos, travel plans or her activity stream that gets created by recent software like Jaiku or Twitter.

Handling friends and acquaintances in such an environment opens up new challenges that are explored by means of a visual prototype. Different types of displaying, managing, and enriching information about related persons are developped. Results from a user testing will be provided.
As a preliminary study, the data sets of several people have been analysed and plotted into an interactive diagramm in order to investigate the potentials of the communication data given. It also offers the possibility to look for the relevant parameters that determine different types of relations (e.g. best friend or old friend).

To provide a conceptual background, existing social network theories are explored and related to personal, ego-centric ones. I take a closer look onto the whole process of operationalisation, i.e. turning human behaviour into quantifiable data by statistical methods. Finally, implications and problematic consequences of both, the software itself and the concept of the „network society“ in general, are discussed. The felt need to turn our friendships into „social capital“ is one of the most remarkable shifts in the functioning of our societies. Others can make draw profits from this capital if they collect detailed data to establish profiles of us and our relationships. Thus, the whole field of privacy is entangled.
And across all these dynamics, computers become so inseparably intermingeld into our daily social life that borders between our (extended) self and the machine is often hard to determine.

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