Creating Social Queues in Cyberspace.

A few weeks ago I talked about activity streams and the valuable context it can provide for social analytics (Activity Streams: Information Highway of the Future?) and in this blog entry I wanted to explore one such scenario.

In todays globally distributed organizations, we spend a lot of our time collaborating with colleagues across countries, relying heavily on technology to faciliate these interactions. One of the many challenges with remote working is the lack of personal connection between people. It’s hard to build a relationship with a colleague when you are separated by five thousand kilometers of telephone lines. All social queues are completely lost — those unspoken messages that we take for granted in face-to-face interaction, such as knowing when someone needs help from that look on their face, or when they need space by the way they are sitting at their desk.

Is there any way that Activity Streams and Social Analytics can make up for this loss of visual social queues and translate those unspoken messages into something we can see within cyberspace?

Just imagine if…

  • All my activities (e-mails, document checkins, calendar events, meeting minutes, wiki comments, instant messages, microblogs, …) are shared on my personal activity stream.
  • There was an analytics backend that ingests & analyzes my activity stream, and becomes my own personal assistant in cyberspace, my Smart Assistant.
  • My Smart Assistant knows (through analyzing my activity stream) exactly what is going on in my work life — what I am working on now? who am I working with? what do I need to do next? do I need help? Am I busy? Do I need a break? Am I going on vacation? — plus anything else I choose to share with it.
  • My Smart Assistant is able to share, on the enterprise activity stream, some of these abstracted insights with the broader community. Some insights may be visible & public — I am currently looking for information on TopicX — while others may be obfuscated (unspoken signals) — don’t bother me… unless.
  • My Smart Assistant is able to ingest information from the enterprise activity stream that may be relevant to what I am working on.

So I now no longer get annoying and inconsequential interrupts because my smart assistant knows when to interrupt me and when not to, and she also knows when I need help. For example; if I am working on a software defect and a similar defect is fixed (a code check-in event), then I would like to get that interruption/help. However if I am preparing for a customer presentation tomorrow morning, then don’t bother me… unless its an important news item relating to this client.

This idea of a Smart Assistant is not new. In fact, the very first time I shared this idea was back in 2006 at the Lotusphere Innovation Lab as part of our work with the Nepomuk EU Framework 6 project, see Galaxy: IBM Ontological Network Miner. At that time we didn’t have activity streams which limited the scope of our work to e-mail interactions. Today, we now longer have those limitations. With activity streams we now have more interactions to analyze and a mechanism to share those insights with people and applications across the entire enterprise. Plus we have oodles more analytics fire-power on the backend through our bigdata infrasructure. Fun times ahead!

2 Comments to “Creating Social Queues in Cyberspace.”

  1. Marie, what you are looking for is an help for a “task overloading” and not only for a reduced “information overloading”. During last 20 years
    our main focus has been information and data and our holy Grail was to reduce the quantity of them to evaluate and consider.
    We need know to move to a level in which the focus should be our “tasks”, a much more complete concept that includes data, information, as
    well as the “activity stream” that are specifically connected with them.
    To give you an example, you Smart Assistant not only should know (and learn) the content but also the list of steps you typically activate
    to manage such content and use it. Our Assistant needs multiple learning strategies, multiple problem-solving abilities, hypothesis generator
    and lastly … a good dose of humour! You know, this last one, is the fundamental fuel that helps us to learn the correct sequence
    of activity steps in our life to follow, driving our by try and error paradigm..


    • There has been lots of discussions around using Activity Streams for executing light-weight ad-hoc processes and I would definitely agree that learning those processes from observing the activity stream, and hence providing support for people around said processes, is a really good application of analytics.


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