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Posts Tagged ‘IBM Beehive’

To what extent does your company facilitate social networking between employees split by geographical or organisational distance, or with (existing or potential) clients and business partners?  What’s the value of this social capital to the company (i.e. the connections within and between social networks as well as connections among individuals).  How does it change the nature of opportunities and constraints each person faces, and the flow-on effects to the team and company as a whole?

IBM recently published its research surrounding Beehive (an experimental internal platform designed to blur the boundaries of work and home, professional and personal, and business and fun).  The report provides empirical evidence of the power of nurturing social capital in the enterprise. IBM Social Networking Research.pdf

The researchers studied issues associated with adoption, usage, motivations, and impact of social networking in the workplace, and they found that:

[E]ven with limited use of Beehive, over a relatively short amount of time, there are associations between types of usage and … different types of social capital. When someone is using Beehive for meeting new contacts, they report a greater interest in making these types of contacts at the company in general.

When someone is using Beehive for keeping up with known colleagues, both in their workgroup and in their extended network of loose ties, they report having closer ties with their immediate network (bonding social capital), a higher sense of citizenship (willingness to help the greater good of the company), and greater access to both new people and expertise within the company [(bridging social capital)].

And finally, the more intensely someone uses Beehive (meaning more frequent visits and stronger associations with the community on the site) the higher they report their social capital is, across all measures. They have closer bonds to their network, they have a greater willingness to contribute to the company, they have a greater interest in connecting globally, have greater access to new people, and a greater ability to access expertise.”

As IBM has illustrated with its customised Beehive-development, supporting social networking in the organisation means more than simply bring in-house functionality from (public) social networking tools.

Instead, social networking functionality should be integrated not only with existing information systems, but also with the particular needs of the organisation to enable people to grow informal networks which exist alongside formal structures, and fully exploit the wealth of information and expertise circulating in and around the organisation.  The latter is very difficult for public social networking sites to deliver.

As with any change initiative, building the right adoption models are equally important as building the right architectural/technical models.  Adoption models raise important issues around the situation of social tools, control of people’s (private) information/discussions, and building on existing networking behaviours, to ensure that levels of information flow and control match needs, cultures and expectations.

Here are a few thoughts in that regard:

  • Well ‘situated’ social tools: This is a concept that we’ve talked alot about (e.g. here, here and here) as it helps in lowering the barrier to adoption.  By ensuring the networking platform is well integrated with key existing information systems and social tools, as people contribute and work with information, trails are automatically created, which when aggregated in profile/personal pages, automatically reflect people’s social network and information connections.  The information is constantly refreshed and kept current without extra effort on the part of the individual user.  People can readily identify who’s working with who on what, or who is connected with who and may be able to make an introduction or support a proposal/project idea.
  • Technology and communication preferences: To maximise involvement, tools need to be made available which reflect people’s preferences for technology and communication style.  As we are seeing from the public domain, there should be a greater emphasis on presence sharing, status updates and other ad hoc style exchanges during people’s work, which can be rapidly embellished and/or responded to by others.  These quick fire exchanges can then form a feed of information in the same way that friendfeed streams information.
  • Professional and personal ‘identities’:  For some people, the line between professional and private lives is increasingly opaque.  But we can’t assume that professional and personal identities will merge comfortably.  As Doug Cornelius points out, as colleagues and clients become friends, we may want to share information with them that we don’t want to share with others.  In the same way that some people use Facebook to keep in touch with their freinds and LinkedIn for their business contacts, people should have the ability to manage ‘professional’ or ‘public’ and ‘private’ profiles in a way which suits their desired level of openness or privacy.
  • Intelligent social networks:  To be even more useful, the networking systems needs to give us a little bit of extra information – like a pat on the back for having participated.  For instance we should see not only ‘who is connected with who’, but also the proximity of people’s connections based on shared attributes, such as tags, groups, communities, and signals based on RSS from social news-reading and interactions (e.g. visits to or comments on posts).  So if we give a little we get alot.

Adoption issues aside, another sticking point for getting top-down buy-in for a social networking project in the company is the difficulty of measuring the value that social capital.  This was one of the caveats the IBM research team highlighted in their report, i.e. the results are indicative of a relationship between use and the measures they used, but are not causal.  As Bill Ives rightly points out, the next steps for us will be to see how we can illustrate the relationship with improved performance and bottom line results.  Your thoughts on this as always are welcome!

Thanks to Bill Ives for reporting the IBM research.

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Yesterday, I mentioned how Cleary Gottlieb had borrowed knowledge engineering techniques from the military, to capture the expertise of senior staff, embed it in a computer system and pass it on to junior lawyers online, in the form intelligent online textbooks and knowledge maps. But I was left wondering about the system’s interactivity, intelligence, and the currency of information therein.

Today, having read about iLink – another military-funded project – I’m now wondering if the Cleary Gottlieb system incorporates any of the social-networking ‘AI’ features mentioned in that article (given the military connection!)?

iLink was developed as a part of the SRI-led CALO (Cognitive Agent that Learns and Organizes) programme and was funded and managed under DARPA’s PAL (Personalized Assistant that Learns) programme.  Mark Rutherford reports that:

iLink is a machine learning-based system that models users and content in a social network and then points the user to relevant content, discussions, and other network members with shared interests and goals across a broad range of scenarios.

To do this, the system uses message-matching technologies for finding related information, and algorithms for gathering data from multiple sources and compiling it together, whilst differentiating private information from that which is safe to share.

Now certain of those technology features/capabilities don’t sound too removed from some social software tools currently on (or almost ready for) the market.  For instance there’s:

  • Newsgator ES – has smart feeds and recommendations.
  • PagesPlus – allows content to be pushed out to the categories and pages corresponding to the tags, and to the users who are subscribing to feeds from those categories.
  • IBM’s Beehive – currently in the research phase – with the capability to ‘recommend’ connections based on activities, tags, bookmarking, etc.
  • Zemanta – blog posts, articles or web pages are directly “read” by Zemanta, which recognizes all contextual content. It then combs the web for the most relevant images, smart links, keywords and text, instantly serving these results to the user to enrich and inform their content.

Nevertheless, it is iLink’s learning capabilities, and SRI’s work in modeling how real-time, dynamic social networks communicate and cooperate to solve problems, that really spark the imagination.  Sarah Perez indicates that the technology:

[has been] used to develop a system for FAQ generation within a network – they call this technology “FAQtory”. With this technology implemented on a social network, FAQs are continuously generated and revised by the community using a Wikipedia-like model, as opposed to being static creations made by the site’s authors. [But it’s no ordinary user-generated FAQ system] – instead, iLink’s FAQtory technology allows for incremental bits of information [to be added] – even those that don’t qualify as answers to the question. As the members contribute these bits of information, the learning system in iLink monitors how users are [attempting] to resolve queries and is then capable of drafting off the social network’s learning.

Potential commercial benefits and applications of such learning technology abound in business. Like expertise identification, comprehensive client information aggregation and delivery, FAQ generation and smart RSS filtering.  As members of, and information in, social networks increase exponentially, there is a growing need to move away from search and retrieval models of information and expertise location.  This is where smarter social technologies will help to streamline the process of recommending, and delivering, information and expertise (as well as filling-in information gaps as they go) to help people get their jobs done more effectively and efficiently.

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