Our goal with Brandfeed is to connect brands and the media more effectively. There are similar efforts on both sides of this fence, but our approach is to provide a centralised database of pressrooms with a journalists’ dashboard all under one roof. The idea as that our pressroom format will become familiar to journalists, so they always know where to go when the they need a media contact, logo asset, or hi-res photo of a CEO. Additionally we offer discovery and notification features so journalists can ‘follow’ the brands they’re interested in, receive content and suggestions in a low-noise environment that they control.

With Dan’s experience in brand communication strategy and my background in tech and creative, we think this is going to be pretty special.

We’re not ready to launch yet, but yesterday we went public. It’s great to be out; I no longer have to say “I’m working on this thing I can’t tell you about yet“. I’m a great believer in transparency and not keeping ideas to yourself, but that’s another blog post

We’ll be giving private previews of Brandfeed to industry friends very soon. After we iterate from that round of feedback we’ll be running a more public beta programme. If you’re a journalist, brand representative or PR you can register for the beta now.

Update – 06 Aug
We are now in a public beta phase.

Datasift (a new product by Tweetmeme, currently in rather exclusive alpha) offers sentiment analysis as part of their streaming filters for Twitter.

Valley-based Fflick are developing their own sentiment engine via machine learning algorithms. The current manifestation of this is a movie review site, but they will be pursuing other verticals – no doubt once the tech has improved and they’ve got some $$s.

Qwiki, which I wrote about yesterday, appears to be on the artificial intelligence trail too. The task of establishing whether content is relevant/important/canonical is an incredibly daunting task to automate.

Finally [prompting this post] this morning I see a product launched by Lewis PR: Chatterscope monitors brand mentions and performs sentiment analysis – A free alternative to Radian6 and Alterian, perhaps? Monitoring and alert functionality is obviously useful, but sentiment analysis – that’s the marketing holy grail, and I’ve always been sceptical.

It’s complicated

Chatterscope’s sentiment engine appears to be little more than keyword proximity matched against a list.  I’m not going to berate them, because if a PR agency came to me with this brief and a few thousand pounds, they’d end up with something very similar. It’s a very hard problem to solve – personally I’m not sure I’d attempt to solve it.

Last Christmas I wrote a simple app (called the XmasFactor) that identified who [on Twitter] was in a Christmassy mood. It was very obvious, very quickly, that it was going to be hugely flawed.  Just mentioning “jingle bells” does not imply sentiment – “Jesus, I wish they would stop singing jingle bells”. It was only a bit of fun, but that won’t stop people calling you out when something doesn’t work.

The complexity of language is such that words alone do not always indicate sentiment accurately. In the first instance, you need to parse a sentence to infer meaning into the mere words. We’re talking about a pretty big margin of error here. Consider -

• Grammar: “Far from the best phone on the market”
• Sarcasm: “No reception in here. great, thanks Orange”
• Context: “Great big scratch on my iPhone”
• Slang: “The new iPhone is bad ass”

It’s clear that these problems require human-like thinking – the kind of thinking that comes from learning. Continual learning, because human culture itself is a moving target. Fflick have people with PhDs in artificial intelligence developing learning machines. I consider myself a good developer, but this kind of stuff is so far out of my league, it makes my eyes water.

Intelligence

There are numerous products and software libraries that provide the natural language processing required for this kind of analysis, so it’s not entirely beyond the reach of the rest of us. However, the fact that a company like Fflick is developing its own technology, suggests these tools have a long way to go, and there’s a lot up for grabs.

Companies tend to be shady about what third party software they use, because [I'd imagine] this knowledge may expose weaknesses in their products, as well as making life easier for their competitors. It appears common for firms to say “we’ve developed our own algorithm” — The allure of the ‘trade secret’.

Nick Halstead of Tweetmeme [when asked at DevNest]  wouldn’t say what sentiment engine was employed in Datasift, but alluded to some third party software being used. (anecdotal, sorry, but I was there).

[Update: Datasift tweeted that they use Lexalytics]

I am told that Alterian developed their own engine, and employ some human-power, i.e. some manual analysis. Radian6′s algorithm was apparently built in-house, whatever that means. And their dashboard seems to provide some sentiment tuning using a human-powered thumbs up/down approach. (I’ve not used either product).

Fflick also use some human-power via Amazon’s Mechanical Turk, although this is only to teach the machines, not to process the live data. See this video for some great insights into Fflick’s technology.

Good luck to anyone working in this field. Personally, I’m more interested in harnessing people power. Social networks give us this in abundance, and until artificial intelligence is truly accessible to me as a developer, I’m steering clear of it. Moreover, I’m not writing any cheques that my code can’t cash.

The @gmp24_7 account (parodying the official Manchester Police accounts @gmp24_1 -through- @gmp24_6) was created at 9:55 this morning and less than 40 tweets later at 10:42 was ordered (by the police, via Twitter) to stop using their copyright

What amuses me about this the most is that copyright infringement is what they got called on. (Apparently falsely according to lawyer @davidallengreen – unless he’s a spoof too). Personally, if I was told I may be impersonating a police officer I’d be a little more petrified.

For the record, this spoof account made no attempt to indicate it was a parody. That was a bit of an error, but they’re still tweeting apparently. I’m curious to see whether Manchester Police take any further action to shut this account up. Most famously @BPGlobalPR remained operational throughout BP’s recent PR crisis.

I look forward to the social media/PR pundits tearing this campaign to pieces. It seems rather brave to enter the public domain with something like this and not expect a backlash.

In my view, this campaign basically says “See, we’re working hard. Don’t cut our budgets“. Does anyone doubt that the police work hard? I don’t. The campaign in no way highlights the actual impact of budget cuts – other than more PR will be done on Twitter, because it’s cheap.

> http://www.webdevgeekly.com/r/www.webdevgeekly.com/mp3/geekly6.mp3

I should clarify a few things for anyone listening:

1. I did get a rude email from Douglas Crockford, but not nasty or in any way aggressive. When I very politely asked for his opinion on the project he responded: “I don’t care for ActionScript“; No “hello”, no signature… Call me old fashioned, but I think that’s unnecessarily rude.

2. “I wonder how they’re doing parts of this” (Harmony and ECMA4 gets mentioned)
As any JS evangelist will tell you, Adobe went off and did pretty much their own thing with AS2/3; JAS syntax follows that path as opposed to the current path of ECMAScript. The ‘compiler’ is implemented in pure PHP. You can test the JAS Parser on its own here, or test the full compiler at jaspa.org.uk. Rather than a JavaScript engine, or interpreter like SpiderMonkey that might run in a browser, the JASPA compiler is really a converter which allows you to deploy regular JavaScript to browsers that have no idea how to interpret JAS, or any other super-set of ECMAScript for that matter.

3. Providing libraries that ActionScript developers are used to – e.g. jaspa.net.URLVariables
I do attempt to follow AS conventions where possible. The URLVariables class is a good example, because it is API agnostic. That is to say that it is a rather abstract utility that could be used in DOM scripting, but equally in any other API, such as server side JavaScript for Flash Media Server for example. It is important to note that the JASPA compiler and JAS syntax are not in any may married to these libaries and APIs. It is platform for which anyone is free to develop their own such utilities.

4. Finally to anyone who wants to try out JASPA, please bear in mind that it is a non-commercial project with a single developer who has a full-time job. The “they” is really a “he”. The compiler itself is a beta, and some of the API classes I’ve been putting together are somewhat alpha.

There’s too much ambiguity and room for misconception in a single headline. Online-reading habits being what they are, if you’re not interested in the headline, you won’t read what’s under it. I suppose this is why people use rather abstract strap-lines like jQuery’s “Write less, do more” and “jQuery is a new kind of JavaScript library“.

I don’t think JASPA can get way with statements this abstract, so I’m currently running with:

“Write JavaScript with the expressive power of ActionScript”

Not catchy, I know; needs work. I’ve also put a real-time compiler demo on the JASPA home page to try and get the message across. I may regret this as the compiler uses a lot of juice. Good job it’s not popular