Posts tagged: Television

A Change in How I Want to Use Twitter…

Image representing Twitter as depicted in Crun...
Image via CrunchBase

A while back I watched some video on how to get a bunch of followers on Twitter.  Oddly, at this point in time, I can’t remember why I wanted a lot of followers on Twitter.

The gist of how it worked was one searches Twitter for things that interest them (for me that was stuff involving software development, Web 2.0, and the Semantic Web).  Then they clicked on and followed almost anyone that mentions those things (particularly if they are hashed because that means that that is what the tweet is about).  I say “almost” because there are certain indicators that imply you shouldn’t follow someone.  For instance, if they have only tweeted twice and don’t have a profile picture then they probably aren’t into it enough to follow you back and start a dialogue.   Also, if someone unfollows you you unfollow them in kind.  This opens up a “space” for following someone else (due to the limitations of Twitter following that I now believe in more than ever).

The basic idea is to follow people who share an interest, have a high likelihood of following you back, and have a quality Twitter stream.  Then, in 3 or so days you un-follow the people that didn’t follow you back and try again.  This works…if you want a lot of followers (and don’t mind following a bunch of people).  However, I have since found it unsatisfying, and here are three reasons why…

  1. Even though there are millions of people on Twitter and the like, I like to keep the web at least somewhat personal.  Following this many people defeats that.  I now am following far more people than I could ever keep up with and am thusly not keeping up with any of them.  There are a small number of people that I would like to follow and keep up with but their streams have since drowned in Twitter chaos.
  2. With the exception of a small number of Twitter streams I find more use in following things not people.  For instance, I used a term in a previous post called “Twitter Sniffing”.  This means to continually monitor a particular search on twitter (such as #Lost for the Lost TV show) and see what updates there are concerning it.
  3. If you think that a lot of people following you means you have a lot of people that will get your tweets…you’re wrong.  Most of the people who follow you back using this method are already following so many people that you aren’t even on their radar.  Using a hash tag will actually work better because people monitoring that subject will read it and they are who you WANT to read it.

So, in short, I got wrapped up in following and getting followed.  But, it’s no longer how I wish to use Twitter.  I wish to have a small number of people I follow and spend most of my time Twitter Sniffing subjects with an application such as TweetDeck ,which I also mentioned in a previous post.  And, if others feel the same way, then I won’t need a lot of followers because those that are interest in what I’m tweeting will be sniffing for it using Twitter search.

And I’m hoping if, with the advent of tools like TweetDeck, people are starting to care less about following and followers and more about sniffing for particular subjects.  If you follow someone because 1/3 of their tweets are about a subject that interests you, would you need to follow them if you could just sniff for tweets about that subject?  You would not only get tweets about the subject from people that you aren’t following, but you would only get the interesting tweets from those you are following.

The concept of following on Twitter is based on the original intent of the application as a means by which to keep in touch with your friends in real time…which it can still do.  But, that’s not the main use case anymore.  And, I think more and more people will be following subjects (by continually searching for certain keywords and hash tags) more often than other people.

Now…How do I un-follow thousands of people without looking like a jerk?

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My Lost Twitter Journey

Lost Wallpaper - Colder
Image by Long Zheng via Flickr

Make something simple, and let your users build complexity on top of it based on how they are using it, not based on how you think they will use it.  To me, that’s a good practice when it comes to the collaborative web.  And, the folks at Twitter most likely had that in mind.  And, if they didn’t, they lucked out.

Wednesday night was Lost night.  And, given the fact that my wife has lost interest in the show, I had to look for excitement elsewhere.  So, I went to Twitter.  And, after desperately twittering about my love of Lost from the virtual mountain tops, I wasn’t having a lot of luck.  Most of my followers either weren’t interested or my words were lost amongst all the other tweets.

So, I tried a few things.  The first thing I tried as going to Twitter Search and searching for “Lost night”, and following a bunch of other “losties” twittering from the mountain tops.

Unfortunately, now I was permanently following a bunch of people just so that one night a week I would have Lost companionship.  And, their tweets were already going to be buried within a bunch of other tweets.  I’m following a lot of people now.

Enter TweetDeck

TweetDeck is a nifty little program that is basically a twitter command center.  And, I had an inspired thought about how to use it along with a convention known as hashtags.  You probably already know what tags are.  The are simply words used to describe or categorize something on the web to make it more searchable.  Tweets contain hashtags with a ‘#’ followed by the tag name.

Below is screenshot along with my annotations:

In the above screenshot, there are three panel that are circled.  Each panel contains tweets based on a particular filter, except for the TweetScoop panel,which I’ll explain below:

From left to right…

  • Replies to me – filtered based on the ‘@purecognition’ being located at the beginning of the tweet.
  • TweetScoop - A tag cloud showing me what terms are popular based on how often they appear in tweets.  Their size indicates their amount of usage.
  • Lost Tweets- filtered based on ‘#lost’ appearing in a tweet.

So, for all intents and purposes, a Lost chat room is molded from the ether simply by enough people collectively using the hashtag #lost.  I can read their tweets, reply to them, and get their replies in my reply panel.  I can also see what topics are gaining the most prominence at any point in time during Lost with the tag cloud.

One interesting thing that happened was during a scene where a character said something to the effect of, “I guess we aren’t going to Guam.”  It amused so many people that a lot of them tweeted his words.  And, over in the tag cloud the word “Guam” got HUGE!

I literally got to watch a piece of the English speaking world watch Lost.  This really hightened the experience, especially due to the fact that it was already a really good episode.

At the end of the episode, one of the Twitterers invited everyone back to his place to chat and listen to a live video of a Lost discussion at a sight called Generally Speaking Production Network.  It was like in college when you are at a bar and someone says, “Hey, we are heading over to a party, wanna come?”

I didn’t stay long, as I had work in the morning.  But, before going to bed, I checked out my counter on my blog.  The counter said 316, which was the name of the Lost episode.  Lost and coincidental numbers go hand-in-hand, thus making that little coincidence a great deal more omenous and a great ending to a formative collaborative web experience.

Lost has a prominent place in the Web 2.0 world.  If you want to see this, just look at this article.  Also, go to Lostpedia and The Lost Experience.

I realize that Lost, as super awesome as it is, is a TV show.  So, I hope using it to make the point at the beginning of this blog entry didn’t trivialize it.  The experience is important because it was organically created by the following:
Twitter + Established Conventions such as HastTags + Twitter API + TwitDeck = My Lost Twitter Experience.  Not by one single centralized organization, but by decentralized communities of users, developers, and fans.

Very cool.

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Opps…It’s a stack, not a queue…

Analogies are used in computer science all the time.  And, one application of them is in data structures.  A stack data structure means that the items are taken off in the opposite order that they are put on…think of the dishes in a buffet.  A queue data structure means that the items are taken off in the same order that they are put on…think of the line at a bank.

I mistakenly forgot that blog posts are on a stack…which means they appear in the opposite order of when I publish them.  So, my series of posts concerning my background are now in the opposite order than intended.  Sorry about that.  In the future, I will take that into account.  For now, if you wish to read about my background, you’ll have to from the bottom up.

Sorry for the inconvenience.

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