You are what you Tweet

Someone once said to me that if you do something once, it’s an accident. Do it twice and it’s a coincidence.  Do it three or more times and that’s just the way you’re living. The underlying message is that if you repeat something enough, then the patterns of use start to tell their own story. Your repeated activity starts to build up into a pattern of use and looking at those patterns can often give insights into the activity that are not apparent by looking at the individual instances of the activity.

This idea of allowing data to “rest where it lays” and deriving insights from it is essentially the idea behind tag clouds, whose patterns reflect repeated use of words, tags, keywords or ideas.  If you look at someone’s Delicious tag cloud and see the patterns emerging in the form of highlighted, emphasised words, then you see a clear indication of what interests that person.  The more they bookmark using tags, the more evident their interests.  The numbers don’t lie when there are enough of them.

if you aggregate enough tag clouds you start to get an insight into the “patterns of the patterns” – you see not just the interests of individuals emerging, but the interests of the group. This is the whole notion of a folksonomy, and it taps into the fascinating concept of the “wisdom of the crowds”.  Data, especially when you have enough of it to form reliable patterns, starts to become very interesting.

In the same spirit, I was a little intriugued by a twitter app I saw today, called TweetPsych.  TweetPsych looks at the contents of your last 1000 messages on Twitter, analyses the words you use and the way your sentences are constructed, and tries to draw conclusions about what you do, what interests you, and what sort of person you might be – psychologically speaking.  I’ve no idea how accurate it might be, but it’s an interesting idea. I’ll be honest and admit to you that I have absolutely no idea what they really mean, but here’s my results anyway… http://tweetpsych.com/?name=betchaboy.

Regardless of whether TweetPsych is accurate and up to scratch just yet or not, I think it signals an interesting development in what is sure to become a much bigger deal.  The notion that some level of machine intelligence can be derived from an analysis of massive amounts of our online footprints.  We are all leaving massive amounts of data behind us as we trawl around the Net, and somewhere in that trail of data there are machines piecing together an accurate picture of us… what we like, where we go on holidays, who we talk to, what our preferences are, and so on.  It’s not a new idea – Google’s entire advertising strategy is based on the concept of knowing more and more about you – but seeing TweetPsych’s attempt at psychoanalysing me from these 140 character snippets of my thoughts just threw it into a new light.

Let’s just hope that this data can be put to use in positive, creative ways that help enhance our lives.

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Finding the Needle in the Twitter Haystack

With millions of Twitter messages floating through the Twittersphere each day, you can use the search tool at  http://search.twitter.com to find references to ANY word that gets uttered there.

So a search for the word “dog” will find every tweet that contains the word dog, and so on.  You can even search for your own twittername and see any time your name is referenced online.  Many companies now use this search feature to find out whenever anyone mentions their products or services on Twitter.

The search tool for Twitter is really quite powerful, and can also be used to generate RSS feeds that can then be embedded into other pages and services.  There is some awesome potential there.

However, Twitter’s ability to search for words being mentioned out there becomes less useful when you search for a really common word, since the search results will invariably turn up lots of stuff you probably don’t want.

When you’re attending a conference for example, you could find every mention that people make about the event by searching for the conference name.  However, it wouldn’t be all that helpful just to do a search on the term “conference” since it would catch all the other possible mentions of the word “conference” from a bunch of other conferences you don’t want. Using the full name of the conference would probably work, but because Twitter limits you to only 140 characters, it would be silly to devote so many of them to including the conference name… there would be little room left for the actual message!

To get around this problem, Twitter users came up with the idea of using a hashtag.. by adding a # in front of a search term. it’s a way to trick Twitter Search into avoiding any results that might contain the keyword but don’t have the hash in front of them.

For conferences, there will generally be a designated hashtag containing a # symbol and an abbreviation for the event. People attending and Twittering from the event can include this short code at the end of each tweet, and then a search (and also an RSS feed) can be created to grab a feed of all the tweets that contain the hashtag, regardless of who they come from. This let’s people follow the conference Tweets in a single stream.

What if the conference has an unusual name already?  A search for a conference abbreviated to “educonf” would probably find most of the references to it fairly easily, since educonf is a kind of “made up” word already.  In this case, a search for the generic term “educonf” or the properly hashtagged “#educonf” would probably turn up pretty much the exact same results.

The real need for the hashtag arises when you have search terms based on regular English words that are ambiguous to the search.  The added # to the front of them makes them unique and helps them stand out from the generic non-hashed word and stops the generic words from getting caught up in the hashtagged feed.  It also carries the added bonus that many 3rd party Twitter clients such as Tweetdeck, Tweetie or Nambu can identify the hashtags and use them to create saved searches, making it much easier to follow the stream based on that tag.

Interestingly, the search feature was never a part of Twitter’s original functionality.  Twitter search was done with a third-party tool created by a company called Summize, but the huge potential (and possibilities for future monetization of Twitter) became immediately obvious and Summize was acquired by Twitter for about $15M almost a year ago.  Now the built-in search functionality is a key part of the Twitter experience, and hashtags play an important role in making that experience even more powerful.

CC Image: ‘Haystack Owl
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The Twouble with Twitter

Sorry Twitter… I really like you and all, but this little video has quite a bit of truth to it. Funny too!

Did I mention that someone I know sends out tweets, on average, including sleep time, every 8 – 10 minutes? Needless to say, I don’t actually follow them.