Some thoughts on working out who to trust online

Some thoughts on working out who to trust online

The deplorable attempts to use social media (and much of the mainstream media’s response) to find the bombers of the Boston marathon and then the tweets coming out of the Social Media Summit in New York got me thinking again about how we might get a better understanding of who and what to trust online.

When it comes to online trust I think there are two related questions we should be asking ourselves as technologists:

  1. can we help people better evaluate the accuracy, trustworthiness or validity of a given news story, tweet, blogpost or other publication?;
  2. and can we use social media to better filter those publications to find the most trustworthy sources or article?

This second point is also relevant in scientific publishing (a thing I’m trying to help out with these days) where there is keen interest in ‘altmetrics‘ as a mechanism to help readers discover and filter research articles.

In academic publishing the need for altmetrics has been driven in part by the rise in the number of articles published which in turn is being fuelled by the uptake of Open Access publishing. However, I would like to think that we could apply similar lessons to mainstream media output.

MEDLINE literature growth chart

Historically a publisher’s brand has, at least in theory, helped its readers to judge the value and trustworthiness of an article. If I see an article published in Nature, the New York Times or broadcast by the BBC the chances are I’m more likely to trust it than an article published in say the Daily Mail.

Academic publishing has even gone so far as to codify this in a journal’s Impact Factor (IF) an idea that Larry Page later used as the basis for his PageRank algorithm.

The premiss behind the Impact Factor is that you can identify the best journals and therefore the best content by measuring the frequency with which the average article in that journal has been cited in a particular year or period.

Simplistically then, a journal can improve their Impact Factor by ensuring they only publish the best research. ‘Good Journals’ can then act as a trusted guides to their readership – pre filtering the world’s research output to bring their readers only the best.

Obviously this can go wrong. Good research is published outside of high impact factor journals, journals can publish poor research; and mainstream media is so rife with examples of published piffle that the likes of Ben Goldacre can make a career out of exposing it.

As is often noted the web has enabled all of us to be publishers. It scarcely needs saying that it is now trivially easy for anyone to broadcast their thoughts or post a video or photograph to the Web.

This means that social media is now able to ‘break’ a story before the mainstream media. However, it also presents a problem: how do you know if it’s true? Without brands (or IF) to help guide you how do you judge if a photo, tweet or blogpost should be trusted?

There are plenty of services out there that aggregating tweets, comments, likes +1s etc. to help you find the most talked about story. Indeed most social media services themselves let you find ‘what’s hot’/ most talked about. All these services seem however to assume that there is wisdom in crowds – that the more talked about something is the more trustworthy it is. But as Oliver Reichenstein pointed out:

There is one thing crowds have a flair for, and it is not wisdom, it’s rage.”

Relying on point data (most tweeted, commented etc.) to help filter content or evaluate its trustworthiness whether that be social media or mainstream media seems to me to be foolish.

It seems to me that a better solution would be to build a ‘trust graph’ which in turn could be used to assign a score to each person for a given topic based on their network of friends and followers. It could work something like this…

If a person is followed by a significant number of people who have published peer reviewed papers on a given topic, or if they have publish in that field, then we should trust what that person says about that topic more than the average person.

Equally if a person has posted a large number of photos, tweets etc. over a long period of time from a given city and they are followed by other people from that city (as defined by someone who has a number of posts, over a period of time from that city) then we might conclude that their photographs are going to be from that city if they say they are.

Or if a person is retweeted by someone that for other reasons you trust (e.g. because you know them) then that might give you more confidence their comments and posts are truthful and accurate.

PageRank is Google's link analysis algorithm, that assigns a numerical weighting to each element of a hyperlinked set of documents, with the purpose of "measuring" its relative importance within the set.

Whatever the specifics the point I’m trying to make is that rather than relying on a single number or count we should try to build a directed graph where each person can be assigned a trust or knowledge score based on the strength of their network in that subject area. This is somewhat analogous to Google’s PageRank algorithm.

Before Google, search engines effectively counted the frequency of a given word on a Webpage to assign it a relevancy score – much as we do today when we count the number of comments, tweets etc. to help filter content.

What Larry Page realised was that by assigning a score based on the number and weight of inbound links for a given keyword he and Sergey Brin where able to design and build a much better search engine – one that relies not just on what the publisher tells us, nor simply on the number of links but on the quality of those links. A link from a trusted source is worth more than a link from an average webpage.

Building a trust graph along similar lines – where we evaluate not just the frequency of (re)tweets, comments, likes and blogposts but also consider who those people are, who’s in their network and what their network of followers think of them – could help us filter and evaluate content whether it be social or mainstream media and minimise the damage of those who don’t tweet responsibly.

Interesting stuff from around the web 2009-04-22

Amazing render job by Alessandro Prodan
Amazing render job by Alessandro Prodan

The open web

Does OpenID need to be hard? []
Chris considers “the big fat stinking elephant in the room: OpenID usability and the paradox of choice” as usual it’s a good read.

I wonder whether restricting the OpenID providers displayed based on visited link would help? i.e. hide those that haven’t been visited? It clearly wouldn’t be perfect – Google isn’t my OpenID provider but I visit lots, but it should cut down some of the clutter.

Security flaw leads Twitter, others to pull OAuth support []
The hole makes it possible for a hacker to use social-engineering tactics to trick users into exposing their data. The OAuth protocol itself requires tweaking to remove the vulnerability, and a source close to OAuth’s development team said that there have been no known violations, that it has been aware of it for a few days now, and has been coordinating responses with vendors. A solution should be announced soon.

Twitter and social networks

Relationship Symmetry in Social Networks: Why Facebook will go Fully Asymmetric []
Asymmetric model better mimics how real attention works…and how it has always worked. Any person using Twitter can have a larger number of followers than followees, effectively giving them more attention than they give. This attention inequality is the foundation of the Twitter service… The IA of Facebook does not allow this. Facebook has designed a service that forces you to keep track of your friends, whether you want to or not. Facebook is modeling personal relationships, not relationships based on attention. That’s the crucial difference between Facebook and Twitter at the moment.

When Twitter Gets Weird… [Dave Gorman]
“The difference between following someone and replying to them is the difference between stopping to chat with someone in the street or giving them a badge declaring that you know them. One is actual interaction. The other is just something you can show your friends.” Blimey – Dave Gorman clearly has a much better grasp of life, the web and being a human than the two people who attacked him for not following them on Twitter. As Dave points out he hopes that Twiiter doesn’t descend into the MySpace “thanks for the add’ nonsense”. Me too.

Google profiles included in search results [googleblog]
A new “Profile results” section will appear at the bottom of a Google search page, when it finds a strong match in response to a name-based search. But only in the US. To help things along remember to use rel=me elsewhere (here’s how).

Shortlisted for a BAFTA, launch of clickable tracklistings and the start of BBC Earth

Look, look clickable tracklistings, w00t!
Few will every know the pain to get this useful little (cross domain) feature live.

We’ve been shortlisted for an Interactive Innovation BAFTA
The /programmes aka Automated Programme Support project. So proud.

Out of the Wild []
Our first tentative steps towards improving the BBC’s online natural history offering. Out of The Wild seeks to bring you stories from BBC crews on location. Eventually this should all form part of an integrated programme offer.


Biological Taxonomy Vocabulary
An RDF vocabulary for the taxonomy of all forms of life.

On url shorteners []
Joshua Schachter considers the issues associated with URL shortening. Similar argument to the one I put forward in “The URL shortening antipattern” but with some useful recommendations: “One important conclusion is that services providing transit (or at least require a shortening service) should at least log all redirects, in case the shortening services disappear. If the data is as important as everyone seems to think, they should own it. And websites that generate very long URLs, such as map sites, could provide their own shortening services. Or, better yet, take steps to keep the URLs from growing monstrous in the first place.”

Identity, relationships and why OAuth and OpenID matter

Twitter hasn’t had a good start to 2009, it was hacked via a phishing scam and then there were concerns that your passwords were up for sale and that’s not a good thing; except there may be a silver lining to Twitter’s cloud because it has also reopened the password anti-pattern debate and the use of OAuth as a solution to the problem. Indeed it does now looks like Twitter will be implementing OAuth as a result. W00t!

touch by Meredith Farmer (Flickr). Some rights reserved.
Day 68 :: touch by Meredith Farmer (Flickr). Some rights reserved.

However, while it is great news that Twitter will be implementing OAuth soon, they haven’t yet and there are plenty of other services that don’t use it, it’s therefore worth pausing for a moment to consider how we’ve got here and what the issues are, because while it will be great — right now — it’s a bit rubbish.

We shouldn’t assume that either Twitter or the developers responsible for the third-party apps (those requesting your credentials) are trying to do anything malicious — far from it — as Chris Messina explains:

The difference between run-of-the-mill phishing and password anti-pattern cases is intent. Most third parties implement the anti-pattern out of necessity, in order to provide an enhanced service. The vast majority don’t do it to be malicious or because they intend to abuse their customers — quite the contrary! However, by accepting and storing customer credentials, these third parties are putting themselves in a potentially untenable situation: servers get hacked, data leaks and sometimes companies — along with their assets — are sold off with untold consequences for the integrity — or safety — of the original customer data.

The folks at Twitter are very aware of the risks associated with their users giving out usernames and passwords. But they also have concerns about the fix:

The downside is that OAuth suffers from many of the frustrating user experience issues and phishing scenarios that OpenID does. The workflow of opening an application, being bounced to your browser, having to login to, approving the application, and then bouncing back is going to be lost on many novice users, or used as a means to phish them. Hopefully in time users will be educated, particularly as OAuth becomes the standard way to do API authentication.

Another downside is that OAuth is a hassle for developers. BasicAuth couldn’t be simpler (heck, it’s got “basic” in the name). OAuth requires a new set of tools. Those tools are currently semi-mature, but again, with time I’m confident they’ll improve. In the meantime, OAuth will greatly increase the barrier to entry for the Twitter API, something I’m not thrilled about.

Alex also points out that OAuth isn’t a magic bullet.

It also doesn’t change the fact that someone could sell OAuth tokens, although OAuth makes it easier to revoke credentials for a single application or site, rather than changing your password, which revokes credentials to all applications.

This doesn’t even begin to address the phishing threat that OAuth encourages – its own “anti-pattern”. Anyone confused about this would do well to read Lachlan Hardy’s blog post about this from earlier in 2008: -fools/.

All these are valid points — and Ben Ward has written an excellent post discussing the UX issues and options associated with OAuth — but it also misses something very important. You can’t store someone’s identity without having a relationship.

Digital identities exist to enable human experiences online and if you store someone’s Identity you have a relationship. So when you force third party apps into collecting usernames, passwords (and any other snippet of someone’s Identity) it forces those users into having a relationship with that company — whether the individual or the company wants it. If you store someones identity you have a relationship with them. 

With technology we tend not to enable trust in the way most people use the term. Trust is based on relationships. In close relationships we make frequent, accurate observations that lead to a better understanding and close relationships, this process however, requires investment and commitment. That said a useful, good relationship provides value for all parties. Jamie Lewis has suggested that there are three types of relationship (on the web):

  1. Custodial Identities — identities are directly maintained by an organisation and a person has a direct relationship with the organisation;
  2. Contextual Identities — third parties are allowed to use some parts of an identity for certain purposes;
  3. Transactional Identities — credentials are passed for a limited time for a specific purpose to a third party.

Of course there are also some parts to identity which are shared and not wholly owned by any one party.

This mirrors how real world identities work. Our banks, employers and governments maintain custodial identities; whereas a pub, validating your age before serving alcohol need only have the yes/no question answered — are you over 18?

Twitter acts as a custodian for part of my online identity and I don’t want third party applications that use the Twitter API to also act as custodians but the lack of OAuth support means that whether I or they like it they have to. They should only have my transactional identity. Forcing them to hold a custodial identity places both parties (me and the service using the Twitter API) at risk and places unnecessary costs on the third party service (whether they realise it or not!).

But, if I’m honest, I don’t really want Twitter to act as Custodian for my Identity either — I would rather they held my Contextual Identity and my OpenID provider provided the Custodial Identity. That way I can pick a provider I trust to provide a secure identity service and then authorise Twitter to use part of my identity for a specific purpose, in this case micro-blogging. Services using the Twitter API then either use a transactional identity or reuse the contextual identity. I can then control my online identity, those organisations that have invested in appropriate security can provide Custodial Identity services and an ecosystem of services can be built on top of that.


Just wanted to correct a couple of mistakes, as pointed out by Chris, below:

1. Twitter was hacked with a dictionary attack against an admin’s account. Not from phishing, and not from a third-party’s database with Twitter credentials.
2. The phishing scam worked because it tricked people into thinking that they received a real email from Twitter.

Neither OpenID nor OAuth would have prevented this (although that not to say Twitter shouldn’t implement OAuth). Sorry about that.