Here's the scenario. You go to your favorite Twitter search engine to see what's going on in Twitterdom. Assuming you've gone to http://search.twitter.com/, you look down at the Trending Topics to see what's on the minds of Twitteropians. You see the following phrase "Skateboarder Wanted." You're intrigued. You're wondering "what could a skateboarder have done that has him or her wanted by the police?" So you click on the link and get taken to the Twitter search results page. You see a number of postings describing a story from Germany in which a skateboarder is wanted for doing 62 mph in a 50 mph zone.
Okay, interesting enough, but Trending Topic? Hardly! At the time of this writing, there were only twenty postings that matched on a query of 'skateboarder wanted.' So how does a topic with so little interest become a Trending Topic?
To answer this question, let's start by taking a closer look at the results. Of the twenty matching posts, four of them were tweeted by a human, and the other sixteen were tweeted automatically from a feed service such as TwitterFeed.com. TwitterFeed is a terrific free service that Twitalytics uses to automatically submit our blog posts to Twitter. The way that it works is you set up an account with TwitterFeed and provide your Twitter account name and password. You set up a new feed by providing the address of the RSS feed you want to post from. You then set the frequency that you want TwitterFeed to check for new posts. Set it and forget it. It really is a very useful service.
But, as with many things, it is pretty easy to abuse this service. You see, even though the spirit of TwitterFeed is to enable you to tweet *your blog* -- you actually can tweet any blog or RSS feed. So let's return to our wanted skateboarder. That story was posted to Digg where it got enough interest to make it into the RSS feed for popular Digg stories. Now imagine a Twitter account whose only purpose in life is to re-tweet stories as they get published via RSS feeds from major sites such as Digg, TechCrunch, NY Times, CNN and so on.
Here is an example of four such accounts. @headlinenews, @headline_news, @top_news and @breaking_news. There are many others but I chose these as really good examples. What each of these has in common is the intention of tweeting news headlines from major news sources. The aggregation of the disparate sources combined to make a somewhat useful Twitter account. You can imagine that if you followed any one of these, you'd be getting a good cross-section of news stories as they occur.
The problem occurs when many people act on this idea and set up Twitter accounts for automated re-tweets of the same news sources. In the case of the skateboarder story, once the headline made it into the Digg feed, fifteen accounts (in addition to diggupdates who also tweeted the headline) re-tweeted the same exact headline. This barage of tweets dealing with the same subject in a narrow slice of time caused the phrase "Skateboarder Wanted" to achieve the status of a Trending Topic (though that didn't last very long). It really wasn't a hot topic nor did it ever become one (at least not on Twitter).
This phenomenon, which we're referring to as "Twitter Echo," occurs for most of the major news sources. The articles get published in their RSS feeds and then re-tweet accounts automatically multiply the post causing the terms in the headline to immediately spike as a Trending Topic. [Note: the phrase "Twitter Echo" has been used before but hasn't taken hold, so the terminology seems to remain up for grabs.]
Is Twitter Echo bad? Well, it creates additional noise in the system that for the most part isn't resonating with the Twitter audience. The four Twitter accounts mentioned above have a combined following of 516. That's not much. Twitter makes it very easy for a user to sign up for tweets from the news sources of interest that the user cares about. Is there really much added value from someone doing the work of news source aggregation? It's hard to imagine that there is.
Sunday, September 7, 2008
Saturday, September 6, 2008
Trending Topics and Hot Searches -- How Twitalytics is Different
A recent blog post on Twitter's blog Twitter Trends & a Tip talks about the Trending Topics feature of Twitter Search. There's no question about the value of this feature. Twitter Search along with the Trending Topics feature provides a real-time snapshot into what people care about at this very moment in time. This provides a level of insight into current events that was not available anywhere else on the Internet until Twitter came along. That's a very bold statement to make, but it's true.
Another exceptionally powerful tool is Twitscoop. This description is lifted from their about page: "Through an automated algorithm, twitscoop crawls hundreds of tweets every minute and extracts the words which are mentioned more often than usual. The result is displayed in a Tag Cloud, using the following rule: the hotter, the bigger (no joke here)."
Twitalytics could not do what it does without Twitscoop. And using Twitscoop inside TweetDeck is a very handy combination of functionality. One more tool that deserves mention is Twitstat which also offers a tag cloud of hot topics. To be sure, there are other Tweeters out there who are also using the tools described here to report back on the hottest topics such as @twitgeistr (uses Twitstat) and @trendingtopics but @Twitalytics aims to do something much more than just report the hot topics.
Regardless if you're looking at Twitter Search's Trending Topics, or Twitscoop or Twitstat, you're never getting the back story. If the word "earthquake" happens to be hot right now, do you know why? A hot word or phrase is actually of no value to you unless you know what is causing so much interest in that topic.
What all of these other services have in common is that they are powered by automation. Sophisticated algorithms comb through the Twitter stream culling out words and phrases that are occurring at an unusually high rate relative to all other words. Whether this gets reported back as a tag cloud or a simple list, the best that these algorithms can offer are the spiking words, not the understanding to explain the reasons for the spikes.
Twitalytics provides a service whereby a human rapidly performs enough research to quickly determine whether there's any importance to a spiking topic or is it just a statistical anomaly that's of no consequence. Then, upon determining that a hot topic merits the attention of our audience, we put an editorial voice to what is happening and explain why anyone should care.
Our Tweets are written as if our followers are getting these as SMS text messages on mobile devices. The goal of each Tweet is to provide enough information with the allotted 140 characters that we alleviate the need for the reader to have to visit a Web page to become informed. This is very different than how news services operate. They Tweet a news headline that usually provides a teaser but not enough information to offer understanding. This forces the user to visit the accompanying URL to get the complete picture. Twitalytics aims to deliver understanding, not teasers.
Another exceptionally powerful tool is Twitscoop. This description is lifted from their about page: "Through an automated algorithm, twitscoop crawls hundreds of tweets every minute and extracts the words which are mentioned more often than usual. The result is displayed in a Tag Cloud, using the following rule: the hotter, the bigger (no joke here)."
Twitalytics could not do what it does without Twitscoop. And using Twitscoop inside TweetDeck is a very handy combination of functionality. One more tool that deserves mention is Twitstat which also offers a tag cloud of hot topics. To be sure, there are other Tweeters out there who are also using the tools described here to report back on the hottest topics such as @twitgeistr (uses Twitstat) and @trendingtopics but @Twitalytics aims to do something much more than just report the hot topics.
Regardless if you're looking at Twitter Search's Trending Topics, or Twitscoop or Twitstat, you're never getting the back story. If the word "earthquake" happens to be hot right now, do you know why? A hot word or phrase is actually of no value to you unless you know what is causing so much interest in that topic.
What all of these other services have in common is that they are powered by automation. Sophisticated algorithms comb through the Twitter stream culling out words and phrases that are occurring at an unusually high rate relative to all other words. Whether this gets reported back as a tag cloud or a simple list, the best that these algorithms can offer are the spiking words, not the understanding to explain the reasons for the spikes.
Twitalytics provides a service whereby a human rapidly performs enough research to quickly determine whether there's any importance to a spiking topic or is it just a statistical anomaly that's of no consequence. Then, upon determining that a hot topic merits the attention of our audience, we put an editorial voice to what is happening and explain why anyone should care.
Our Tweets are written as if our followers are getting these as SMS text messages on mobile devices. The goal of each Tweet is to provide enough information with the allotted 140 characters that we alleviate the need for the reader to have to visit a Web page to become informed. This is very different than how news services operate. They Tweet a news headline that usually provides a teaser but not enough information to offer understanding. This forces the user to visit the accompanying URL to get the complete picture. Twitalytics aims to deliver understanding, not teasers.
Friday, September 5, 2008
Tweetlog for September 4 through September 5
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