Social Learning: Now Everyone Is An Expert

January 14, 2013 Xyleme

You’re looking for a present, say a new tool for your workshop, and there are a number of options, from different manufacturers and at slightly different price points… Most of us, these days, would check out the reviews – perhaps those on the retailer’s website, or on generic review sites like or from specialist magazines. Some would ask in subject-specific forums, Facebook groups or using a suitable Twitter hashtag. You’re likely to find huge amounts of information, but how do you know which is accurate? Which sources are biased towards or away from particular products?

It’s all about building a network of reliable, trusted sources. And it’s true whether we’re talking about product reviews, news or answers to questions raised on a company network.

That trust can be developed in a three main ways:

  • Your previous experience
  • Other people’s experience
  • The impression the source gives

Only by pulling all three together can you get a really good idea of whether someone who says they are an expert really is an expert. If one or two elements are missing, then the other(s) need to really be strong to support any trust you put in the information you get.

Your previous experience
If you’ve taken information from a particular source before and it turned out to be correct and accurate, then you’re more likely to use and trust them again. The more often they provide good information, then the higher up your trust scale they go. Would you ever rely on just one information source? Well, it depends how high they are up your trust scale, and the importance of the question you’re answering. If it’s a matter of life & death, or national security, then perhaps you’d want corroborating information. If it’s just which hotel to book into, then you might just base it on advice from one good friend who knows what you like.

Other people’s experience
The beauty of the internet is that it allows many people to have an opinion and for that opinion to be collected. We do it all the time for products – basing purchases on the number of favourable reviews. But we can also do it for information, basing acceptance on how trusted that source is by your peers. This tends to happen implicitly rather than through explicit ratings etc (although there’s nothing to stop that – as shown by LinkedIn recommendations).

By implicitly I mean through proxy measurements such as “number of followers” (as seen on Twitter). People who have lots of followers are assumed to be people who are listened to. These people then gain more followers. In network theory, this is the principle that “the rich get richer” (Barabasi: Linked 2003, see: This does mean that you might be following someone just because everyone else does, and not necessarily because they are accurate or trusted. For example, would you trust Stephen Fry (with more than 5,000,000 Twitter followers) for what he has to say on which wood-working tool to purchase?

The impression given by the source
Before trusting a source to give you information, you’ll want to check them out first – to understand their biases, their currency (ie. How up-to-date they are), their experience, their “professionalism”. So much of this is subjective, and, to be honest, some of it is quite easily faked. But the fact that someone has spent time on their website, presents the information well, cites their sources, exposes their history etc all adds to a general impression of trustworthiness.

For a comprehensive checklist, see Cornell University’s Source Evaluation Checklist: Basically the more you know about an information or service provider, warts and all, the more you are likely to trust them.

That’s why I really like Salesforce’s approach: “Success is built on trust. And trust starts with transparency.” At you can find up-to-date information on how well the system is performing and how they’ve built their system to be secure. All essential information if you’re going to trust them with your organisation’s data. But of course, you’d want some external references too!

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