Following the Trend @dbacksbooth on Twitter

Time for another update on the trend line for @dbacksbooth on Twitter. Not much to say beyond the staggering growth in the number of replies to the booth per day. 

I factored out the early spikes in July and mapped a trend line from August 1st through yesterday. I think the results are pretty impressive especially factoring the DBacks record.

More importantly, It looks like the growth is beginning to “hockey stick”… I’m pretty sure the trend will be well above the 80 or so the trend line predicts. Let’s see what happens over the last few weeks of the season.

It is ALIVE – Twitter Search is Back To Full Speed

Not sure what was going on, and there was no mention of it on the Twitter status blog, but it now appears that Twitter Search (and the search API) is back to full speed. There is no question that all day yesterday and and today up until 12:00 Pacific Twitter search was not indexing all Tweets.

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Unless of course all the Twitter users just took an 30 hour nap…

We will keep an eye on it and keep you updated here.

Posted via email from justSignal Status & Updates Blog

Something is DEFINITELY Not Right with Twitter Search

I get hourly emails that show me (graphically) how much justSignal “collects” total from each of the services (Twitter, Blog Search, Backtype, etc). The thing about these graphs is they are amazingly consistent over time – that is why we use them… you can quickly see a change in the normal trend.

Yesterday I noticed that Twitter’s graph looked funny and that the volume was way down from a typical day (on a typical day we collect ~150 thousand tweets). This morning that trend has continued:

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A normal day is a nice smooth curve up from about 2 or 3 am through mid day… like this:

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Also worth noting, our total volume of Tweets collected yesterday was the lowest it has been in 60 days. Normally I would chalk this up to normal variation, but the percentage change from Monday to Tuesday was 50% – and that is unprecedented day over day change. You should also note that http://search.twitter.com provides an exact tweet for tweet match (in our limited sampling) to what we are collecting via the API – so this appears to be a global Twitter Search issue.

This seems to be affecting Trackers with high volume traffic on Twitter – so many of you will not notice any change. If however, your tracker regularly pulls in 10,000 tweets per day it appears that your volume will be cut (roughly) in half.

Obviously all of this is anecdotal and I’ve received no confirmation from Twitter that there is any issue. We will stay on top of it and keep you updated.

NOTE: No, we are not being rate limited – we are, in fact, using less than 10% of our whitelisted request limit per hour. All requests to Twitter Search API are returning normal response codes and, in most cases, tweets – just not nearly as many as just 2 days ago.

Posted via email from justSignal Status & Updates Blog

No @zappos Best Practices Don’t Stifle Innovation…

One of the problems with Twitter is that it encourages trite overly-simplistic statements of fact. Hey, here is one from Tony (@zappos) the CEO of Zappos:

I’m only posting about this because it has been re-tweeted like a bazillion times in the last 3 hours by twitterati proclaiming it’s complete and utter truth. And I’ll grant you, it sounds good… but it isn’t true.

Best practices are a good thing. They let you implement known quantities, limit risk, limit costs and establish a baseline of capability without wasting precious cycle re-inventing the wheel. That doesn’t stifle innovation, it increases margins, lowers costs and saves time.

Can it stifle innovation? Sure, but so can just about anything when you do it wrong. 

The point here is that you have to decide what it is that differentiates your business – those things that are your competitive advantage. That is where you want to invest in innovation. Everyplace else – all those things that don’t differentiate you in the marketplace – are ripe for the application of best practices. 

What stifles innovation is the failure to be cognizant of where you differentiate and the failure to invest in innovation in those areas.

The Growth of @DbacksBooth on Twitter

I’ve been watching the Dbacks broadcast team begin to use Twitter to interact with their audience, and I’ve been using justSignal (shameless plug for my product) to track their efforts. Over the last 60 days I’ve watched the effort from the Booth and (I presume) Fox Sports AZ intensify. They’ve been requesting Keys to the Game and answers to the AFLAC trivia question via Twitter.

The early efforts were marked by significant inconsistency and mixed messages both on air, and on Twitter. Just look at the gaps in the graph below.

That being said, it appears that on August 7th or 8th they began to consistently engage. What impresses me is how quickly the efforts bear fruit. 

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Look at the growth and the consistency of the growth between August 7th/8th and the 29th. There are consistent jumps of 10 – 20 responses per game. 

Two takeaways from this data:

1) Consistency of interaction on Twitter seems to outweigh the on air requests. 
2) A very small investment of time from the broadcast team (4 or 5 tweets) generates a relatively large and consistently growing response.

I know in terms of Fox Sports AZ viewership the numbers are pretty small, but at this point the real goal should be to move the trend line in the right direction. If you look at the trend line for the responses to @dbacksbooth on Twitter it tells you everything you need to know – steeply up and to the right.

They are on to something… and the small investments they are making in Social Media will pay large dividends if they keep this up. The real question is, what will they do with this engagement? I have a few suggestions if they’d like to give me a call.

Teddy Kennedy and Lessons on Bipartisan Politics

When you think about it, what bipartisan politics really requires is quite simple – and Ted Jr. explained it about as eloquently as possible today.

 It is the simple realization that those with whom you disagree love this country just as much as you do. That we don’t have to de-humanize those with whom we disagree in order to elevate our point of view.

 When we stop dividing the good from the evil based on political philosophy and agree that we all share the same goal – a more perfect union – we can have productive debates about the pros and cons of alternate methods for achieving that goal.

 Personally, I’m done with anyone who villifies those with whom they disagree; I will no longer allow the politics of fear and division to have any sway.

 Won’t you join me?

 Sent from my iPhone

The Trouble with Sentiment Analysis

I’ve been involved with Sentiment Analysis and AI processing of text for years (going on 15 now). It was a huge push back in the heyday of CRM with companies like Kana creating Automated Response Tools for email service and support. They were supposed to be magic – just have your customers free-form email your company and Kana would figure out what they wanted and respond with a Knowledge Base article. It was the service/support holy grail. 

Anyone heard of Kana lately?

Maybe you think I’m being an old guy… and I just don’t get it. Maybe you think the algorithms and increases in processing power have brought deriving sentiment and intent from text into the realm of the completely banal – it is easy, and anyone can do it. Maybe, but I’m a sceptic. And here is why.

How many times a week do you have to have a conversation with a family member, friend or colleague in which you attempt to explain what you really meant in that post, tweet, or email? 

How often do you end up having 30 minute conversations because you were defining a key term differently? 

How many times do you search on Google and get stuff you weren’t looking for?

Here is the thing, text is a HORRIBLE CONVEYOR OF SENTIMENT AND INTENT. The reality is humans have a really tough time deriving sentiment and intent from text – never-mind algorithms. Only the very best writers are able to consistently convey exactly what they meant to convey – and I’ll assure you it is because they used far more than 140 characters.

So when you see sentiment analysis being bounced around the Social Media echo chamber – before you buy in and start judging your company, product or brand based on some number spit out by a website, remember the last time you had to tell someone – “I know what I wrote, but that’s not what I MEANT” and proceed with caution.