Posts Tagged ‘trust’

Social Network Analysis – cure or curse?

August 31, 2010

In this blog I am going to outline a highly risky yet potentially foundational part of Knowledge Management and especially Intellectual Asset Management – Social Network Analysis (SNA).

SNA is a method of mapping either the connectivity of concepts (like twitter-feed), or more importantly to us, communication between people (like a kite network).

SNA is a tool of Knowledge Management in general (Tran 2007), but becomes a core aspect of building Communities of Practice (Wenger, McDermott et al. 2002)

The reason that it is highly risky should become self evident as we proceed, but in case I don’t make it clear – it stands a reasonably good chance as being seen as invasive, manipulative, and intrusive, and will alienate the very knowledge workers and staff that you are trying to unite in purpose.

You could very well unite them – against you!

The basic idea is pretty fundamental to Knowledge Management: You want to figure out who your thought-leaders, subject-matter experts, and influencers are by seeing who communicates with whom – the experts are consulted more than they consult others.

In a sense you are using the “well worn path” and letting the activity of staff show you who your SMEs are (or at least who the staff think they are) and the conduits and paths that information and knowledge takes in your organization – both internally and with partners.

Before you go down this path at all, you need to be sure of two things – How you will communicate the program to staff, and what safeguards there will be over the use of the information.

Once you know who is talking to whom, it will be very tempting to use that information for disciplinary actions as well as for knowledge management. This spells disaster because using it just once to nail the office lovers or a gossip, (or even the person leaking company secrets) will easily undermine the further trust of staff in a dramatic and probably catastrophic fashion.

So before you start planning SNA, be very sure that you are going to explain the purpose and the need very carefully as well as making it very clear if content of messages will be sampled, and that no information will be used for any other purpose than knowledge management.

I have split the methods into several categories of ever-increasing accuracy and reliability, but also unfortunately also in escalating levels of intrusiveness.

Non-Intrusive Methods

This is the easy one, simply don’t do anything, or just fish it out of your own memory or imagination.
This is how most organizations do it, and it is just marginally better than a Ouija-board or reading tea-leaves.
It is subject to all the normal human cognitive biases – halo effect, concurrency, freshness, proximity, likeness, and so forth.

If you want to be no better than any other firm, then do it this way.

Partially-Intrusive

This is where you just ask and hope you asked clearly and that the answers are accurate and truthful. You can improve the odds with a well crafted questionnaire of the “Who do you ask” variety.
The biggest problem will probably be the limit of your expertise in building a good questionnaire instrument that has high construct-validity and reliability, and the recall of the respondents. People often don’t recall who they get information from when asked to report them on the spot, and they will suffer the same biases you would – they will tend to remember the most recent more than more frequent but remote events, and some events will be more memorable and overshadow others. They will also tend (like you) to over-sample people they like and people who they perceive to be “more like them”.

This is a valid but somewhat spotty measure.

Intrusive Methods

These sample actual activity and communication traffic rather than relying on people’s memories and willingness to report on their own behavior.

Basically you are going to snoop by monitoring the source and destination of messages, and record who talks to whom by using electronic records captured on office systems:

  • Telephone records
  • Email traffic
  • Instant Message activity
  • Newsgroup activity
  • etc.

Other than the fact that people might object to what they feel is being spied upon, two immediate issues raise their heads with any of these methods – your mapping will be neither exclusive nor exhaustive.

  • Exclusivity
    It will pick up the gossips, the lovers, and the experts alike and without very careful and even more intrusive sampling you won’t easily be able to tell them apart. You simply won’t know if the high traffic between two or more people is due to knowledge exchange for business, a hobby, a secret office romance, or just plain office gossip about who is having a romance in the office!
  • Exhaustivity
    There are several modes of knowledge transfer that it won’t pick up, as well as those SMEs who are reclusive and don’t advertise or signal their competencies. In the former case, people may be physically visiting and consulting the SME, using electronic media that you aren’t monitoring, or contacting them outside the premises or business hours and thereby escape detection.

This is the best way in terms of accuracy and immediacy – it harvests more broadly and without human biases in the sampling and reporting, and it can be updated on the fly.
Some of the tools available also automatically produce very readable and attractive network maps that are easily interpreted compared to lists and numbers.

Often a single glance will show nodes, portals, and hubs – that is people who others go to often, people who connect different groups, departments, or companies, and people who connect other people.

Real, Really Intrusive

This is where you pull a [name deleted] and actually sample the content of message in addition to source and destination. This would allow you to discard a high proportion of private or business-irrelevant messages from the computation and thus tend to exclude the lovers and gossips from the mapping.

It also allows you to automatically build the foundations of a Controlled Vocabulary, and pick up information to build Concept and Topic Maps, and to find both needs and sources for specific topics.

For instance, you might be able to discover that Betty is the expert in Oracle Index tuning and that there is a popular need for Index tuning because there is a lot of and frequent traffic from several sources to Betty using key words in the messages.

Not only could you spot problems and issues and trends as they develop, but also know who needs to be served and who is serving knowledge on the fly. The potential for Just In Time training alone is quite stunning, not to mention the ability to have early detection and rapid response to business problems.

It goes without saying that this level of intrusiveness requires either a Byzantine degree of spying or an extremely high level of trust amongst staff, and whilst it would enable some pretty terrific advances with compound business advantages, it also has the capability to detonate into a big fireball that will rip your organization apart if it ever lost trust.

Really, Really, Horribly Intrusive

Ok, let’s just not go there – wires dangling from people’s bodies is just too dystopian to contemplate and besides, fMRI machines are darned expensive.

Conclusion

Knowing your Social Network Architecture allows you to know who your respected SMEs are, what the communication conduits look like, and how the knowledge in your organization is interconnected – no small achievement!

However, a proper communication plan and careful presentation and execution are vital because the level of intrusiveness can easily lead to a revolt amongst your knowledge workers.

If you use the information in a disciplinary or punitive fashion, you will do more harm in a single stroke than if you had cut wages and perks and fired the office mascot.

Bibliography

Tran, L. A. (2007). Encyclopedia of communities of practice in information and knowledge management .

Wenger, E., R. A. McDermott, et al. (2002). Cultivating communities of practice: A guide to managing knowledge , Harvard Business Press.

Please contribute to my self-knowledge and take this 1-minute survey that tells me what my blog tells you about me. – Completely anonymous.

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Matthew Loxton is a Knowledge Management professional and holds a Master’s degree in Knowledge Management from the University of Canberra. Mr. Loxton has extensive international experience and is currently available as a Knowledge Management consultant or as a permanent employee at an organization that wishes to put knowledge to work.

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Knowledge Management issues: Trust and Information.

March 6, 2010

I was recently asked something that related to information-foraging behaviours of people seeking answers to problems – surely a typical situation of both private and work life. This blog deals with the topic of trust and positions it in the terrain of Knowledge Management.

Because of the question, I am departing briefly from the typical blog format and dealing with this in a more academic fashion, so please excuse the slightly more formal tone.

Introduction

The issue of trust spans many diverse dimensions, and ranges in subject matter from psychologists trying to gauge the reliability of experiments conducted across the web (McGraw 2000) to firms that provide tools and methods to swiftly access sensitive information in times of emergencies such as natural disasters (Trembly 2006).

In this discussion, a broad selection of illustrative situations will be explored in which trust is a salient factor, and specific attention will be given to trust and the web in context of medical information as an example.

Dimensions and facets

Trust spans a multiplicity of facets, not only across different industries, but also in terms of granularity. For example, at a very technical level it involves how Webservices and inter-agent dynamic trust frameworks have to be constructed (Skogsrud 2004), so that different computer systems can interoperate reliably without loss of data.

At a less transactional level, trust also involves how providers of information get information they trust in order to confidently serve that to end users – for example: teachers need to go about evaluating sources for building a curriculum and choosing materials (Vasko 2007).

Back at a technical level there is the matter of Web spoofing, and how to identify if a user is who they claim to be (Herzberg 2005), which obviously is a source of concern to organizations not just in terms of risks to themselves, but taking into consideration that poor access control would degrade the information-esteem in which they are held by their user community. As a client, we would surely be less inclined to use an organization that let somebody pretend to be us.

Trust is also not one-sided, for example firms need to trust what respondents say (Gosling 2004) and therefore some thought is dedicated to proposing a model focused on commitment-loyalty relationships that exist between customer and provider in order to gain customer loyalty (Thatcher 2004)

There are thus several transactional types:

  1. Machine to Machine
  2. User to Organisation
  3. Organisation to user
  4. Organisation to Organisation
  5. User to User

With the advent of peer-to-peer networks and sharing of information in chat rooms, newsgroups, and the like, there are issues of trust involved in taking advice or buying something from somebody who is not representing an organization whose credentials might be widely known.

An example of how community-based trust evolves is eBay, in which user-ratings are displayed for any seller and which all potential buyers can view.

Web2.0 approaches are thus likely to evolve towards a user-driven trust model.

All of these classes seem to require different approaches, but could they all fall under a single unifying structure that deals with trust?

 There is some work on describing “trust frameworks” as such a unifying basis for interaction between agents (Sillence 2006)

Engendering trust

What steps are users and organizations taking to increase or even to use, trust?

Some amount of trust is engendered by the use of secure protocols built into websites. It is commonplace for banks to provide the “https” type pages for transactions, and some libraries are doing the same to encourage trust in their patrons that their information, and information-seeking activities are private and secure (Breeding 2005)

There is also a great deal of use of national or regional “better business” accreditations or “seals” on a website as a way to improve user trust, and it seems that users feel a sense of  relief when these are displayed (Paul 2002).

However, trust also resides simply in the web site appeal and usability, and on the initial “trust beliefs” of new customers (Hampton-Sosa 2005). This hints both at how users come with preconceptions about what a trustworthy site looks like and works like, and raises the question of “appeal”. Are “Smart-looking” sites more trusted? – The suggestion is that they might be, since perceived quality is seen as a strong factor (Hwang 2007)

Morville portrays the market as a “conversation” (Morville and Rosenfeld 2006) in which the relatively static presentation, content, and architecture of a website is engaged in a discourse with the user, and thus communication characteristics between e-vendors and customers in building trust becomes important, and the use and display of policies and “seals” is in fact part of this interplay (Metzger 2006)

Further, customers and users are trying to discern key characteristics gleaned from the web presence that would reveal the organisation’s ability, benevolence, and integrity, and they will use these factors to gauge trust in order to differentiate a firm from less trustworthy alternatives (Lee 2005)

Part of the disclosure that users are foraging for are privacy policy statements on websites, and trust is in  part being built merely on the belief that a firm displaying a privacy policy is more trustworthy (Manon 2007)

Returning to the example of eBay, online communities and other Web 2.0 environments pose new interaction types that must be addressed when considering how to build trust (Swaine 2007), and there is a need for marketing in the new Web2.0 terrain to be handled in a manner that demonstrates authenticity, consistency,  and trustworthiness at a different level than before (Goldie 2006)

“Trust-management” thus becomes a necessary dimension to address when approaching interaction on the Semantic Web (Thuraisingham 2007)

State of trust

So how are things going?

In contradiction to findings that seals and membership of business bureaus engendered trust, McKnight finds that

“…neither a noticeable […] privacy seal nor a noticeable professional association seal had any significant impact on trust” (McKnight 2004)

Costanzo suggests that all the talk about trust, and especially the two-way trust in internet banking might actually engender more uncertainty and doubt, and that simply by drawing attention to the topic of trust, less trust is actually built (Costanzo 2005)

The efforts to create “Trust Building Models” and open discussion of the cognitive cues that users employ in initial trust formation (Wakefield 2004) might then simply engender  a form of “arms race” in which sites compete in “trustability” and untrustworthy providers strive to improve the façade of trustworthiness, and increase use of symbols in order to make people trust them more rather than actually trying to become more trustworthy. The semiotic artifacts of trustworthiness then become the unit of exchange in judging trustworthiness rather than being evidence of actual trustworthiness.

There is some evidence for this – US Newswire reports that users have less trust than previously with regards the web, and advertises a conference on web security (2005) where these disappointing facts would be explored.

At the same time, online drug purchases still lag other products perhaps due to issues of trust (Dubie 2007)

However, it is amply clear that users value trust in both brick and click environments. In a medical context, studies reveal that users express a need to be able to trust a hospital and its website, and are highly interested in both physician credibility, and institutional reputation (Gallant 2007)

However, people are conflicted about this, and while they express a desire to see evidence of trustworthiness, in practice it seems that they seldom look for the evidence.

In the publication Child Health Alert (2006) for example, attention is drawn to the results of a Pew Research finding that 75% of people failed to check the date and source of online health information “sometimes, hardly ever, or never”, and that only 2% of  popularly used health websites include such basic information as publication date and source.

If users were simply avoiding the web in the face of lack of trust it would perhaps be less of a concern, but in spite of wanting and not using evidence, users nevertheless go to the web for medical information viz. 75% of respondents (n=800) report that they consider the web as their “most trusted source for drug information” (McGuire 2007)

This is further borne out in the publication American Nurse where an URAC survey on web user’s trust is discussed with regard health-related and health-insurance websites, and reveals a high level of respondent trust (2001).

Clearly then some conflicting perspectives how users look for signs of trustworthiness, but plainly users desire it, and in many areas do in fact trust web sources.

Information scent and Trust

If we were to lay out some salients of a “Trust Model” based on what has been covered in this discussion, the scent of information-trustworthiness would be engendered inter alia by

  • Use of secure technologies where appropriate, such as secure hypertext transfer protocol.
  • An appealing but appropriate style suited to an already existing institutional reputation for credibility, ability, benevolence, and integrity
  • Display of  tokens and accreditations or seals (even though they may be ignored)
  • Usability based on consistent presentation, content, and architecture that support authenticity, and consistency.
  • Display of policies, especially privacy policy
  • No discussion of trust itself

 

With regards documents or information itself

  • The date of the article is clearly noted
  • The author and credentials are noted
  • Conflicts of interest and memberships are disclosed
  • Sources are correctly attributed

 

Epilogue : The scent of scent

It is notable that in practice many authoritative sources are not much better (if at all) than non-authoritative sources as far as scent markers and signs go. Many official factsheets are undated or have no named author or fail to identify the credentials of an author, make no statements of any conflict of interest, or tokens, or privacy statements.

Likewise, many large and reputable banks outsource credit-card sales to third parties, and this practice effectively teaches consumers to ignore facts that should otherwise make them suspicious – such as different web addresses, different IP domains, and different vocabularies or headings. These are all things that should warn us not to trust the source, but here we have the very people who warn us to be vigilant, encouraging blindness.

The poor maintenance of information-scent by the true authoritative organizations thus undermines the use of scent to warn the user when something is amiss.

It is the duty of organizations and people in positions of authority to make sure that the information they make public coheres to standards of integrity, and that includes ensuring that basic rules are followed that distinguishes their information from mere opinion. By not doing so, they attenuate and confuse the “reference scent” to which other information is compared.

If bad information is to be distinguished from good, it is necessary that the good be a clear and consistent reference point against which we can measure. When authoritative information sources fail to provide a strong scent of authenticity, the non-authoritative sources seem more credible –with potentially devastating results.


Bibliography

 

(2001). “In Web we trust–with some reservations.” American Nurse 33(4): 6.

(2003). “Gastrointestinal diseases.” Communicable Diseases Intelligence 27(1).

(2005). “Consumers Trust Web Sites Less Than Ever, Consumer Reports Webwatch Finds.” US Newswire: NA.

(2006). “Putting Too Much Trust In Health Information On The Web.” Child Health Alert: 3.

Breeding, M. (2005). “Building Trust Through Secure Web Sites.” Computers in Libraries 25(6): 24.

Costanzo, C. (2005). “Does Touting Web Safety Build Trust or Fear?” American Banker 170(118): 14.

Dubie, D. (2007). “Consumers just say no to drugs online; Forrester Research survey shows U.S. consumers don’t trust Web when filling prescriptions.” Network World: NA.

Gallant, L. (2007). “User-centric hospital Web sites: a case for trust and personalization.(Report).” E-Service Journal 5(2): 5.

Goldie, L. (2006). “Brands looking to exploit Web 2.0 need to build up user trust.” New Media Age: 15.

Gosling, S. O. (2004). “Should We Trust Web-Based Studies?” American Psychologist 59(2): 93.

Hampton-Sosa, W. (2005). “The Effect of Web Site Perceptions on Initial Trust in the Owner Company.” International Journal of Electronic Commerce 10(1): 55.

Herzberg, A. (2005). “Reestablishing Trust In the Web.” Dr. Dobb’s Journal: Software Tools for the Professional Programmer 30(10): 28.

Hwang, Y. (2007). “Customer self-service systems: The effects of perceived Web quality with service contents on enjoyment, anxiety, and e-trust.” Decision Support Systems 43(3): r2007.

Izenberg, N. and L. Hirsch. (2007). “Can I Feed My Baby Honey?”   Retrieved 8 April 2008, 2008, from http://www.kidshealth.org/parent/question/medical/honey_botulism.html.

Lee, B.-C. (2005). “Lemons on the web: a signaling approach to the problem of trust in Internet commerce.” Journal of Economic Psychology 26(5): 607.

Manon, A. (2007). “The impact of reading a web site’s privacy statement on perceived control over privacy and perceived trust.” Online Information Review 31(5): 661.

McGraw, K. O. (2000). “The Integrity of Web-Delivered Experiments: Can You Trust the Data?” Psychological Science 11.

McGuire, S. (2007). “Consumers trust Web for drug info.(E-MARKETING).” Medical Marketing & Media 42(9): 26.

McKnight, D. H. (2004). “Shifting Factors and the Ineffectiveness of Third Party Assurance Seals: A Two-Stage Model of Initial Trust in a Web Business.” Electronic Markets 14(3): 2004.

Metzger, M. J. (2006). “Effects of Site, Vendor, and Consumer Characteristics on Web Site Trust and Disclosure.” Communication Research 33(3): 155.

Morville, P. and L. Rosenfeld (2006). Information Architecture for the World Wide Web. California, O’Reilly Media.

Paul, N. C. (2002). “Labels slowly build trust in the Web.” Christian Science Monitor 94(118): 18.

Sillence, E. (2006). “A framework for understanding trust factors in web-based health advice.” International Journal of Human-Computer Studies 64(8): 697.

Skogsrud, H. (2004). “A trust negotiation system for digital library Web services.” International Journal on Digital Libraries 4(3): 185.

Swaine, M. (2007). “Web 2.0 AND THE ENGINEERING OF TRUST.” Dr. Dobb’s Journal: The World of Software Development 32(1): 16.

Thatcher, J. B. (2004). “Commitment, Trust, and Social Involvement: An Exploratory Study of Antecedents to Web Shopper Loyalty.” Journal of Organizational Computing & Electronic Commerce 14(4): 243.

Thuraisingham, B. (2007). “Administering the Semantic Web: confidentiality, privacy, and trust management.” International Journal of Information Security and Privacy 1(1): 18.

Trembly, A. C. (2006). “The Web Vs. The Real World: Who Do You Trust?” National Underwriter / Life & Health Financial Services 110(35): 50.

Vasko, F. J. (2007). “Can Teachers Trust the World Wide Web for Classroom Lesson Plans?” TechTrends: Linking Research & Practice to Improve Learning 51(5): 53.

Wakefield, R. J. (2004). “THE ROLE OF WEB SITE CHARACTERISTICS IN INITIAL TRUST FORMATION.” Journal of Computer Information Systems 45(1): 94.

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Matthew Loxton is the director of Knowledge Management & Change Management at Mincom, and blogs on Knowledge Management. Matthew’s LinkedIn profile is on the web, and has an aggregation website at www.matthewloxton.com
Opinions are the author’s and not necessarily shared by Mincom, but they should be.


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