twitter

Check out this cool how-to video on creating a twitterbot without any programming. It was put together by frinkey.com and I'm proud to say, inspired in part by my code-less NPRbackstory hack.

If you're familiar with NPRbackstory and want to know how it was put together, you can't do better than with this online tutorial.

Internet solutions appear wherever finding, connecting, and sharing information with others is expensive or difficult. This is especially noticeable when individuals with similar interests but insufficient proximity are finally able to connect. Unsurprisingly, there are now sites bringing together global interest in speaking Klingon, knitting food, and collecting cookie fortunes.

But what about deploying internet technologies for people who are near one another? Certainly this technology isn’t just about bringing together far-flung hobbyists – there should be unresolved information needs that exist at a local level, as suggested by the buzz around hyperlocal news.

In determining these information needs, we must resist the temptation to focus on what media organizations proscribe or what is currently vanishing from existing news outlets. Instead, we should look at routine communication barriers that can be dismantled by internet-based solutions. This is surprisingly difficult to do, since we often don't see the barriers we face or recognize them as unnecessary. In order to determine where technology might be best deployed to address local needs, we must find situations where individual members of local communities are actively trying to find, connect, and share information with one another. Then we can look more closely at the difficulties, delays, and expenses that might be eliminated or reduced through more tailored use of online technology.

Looked at in this way, it becomes clear that finding and connecting with others nearby to exchange our stuff (craigslist.org), meet around shared interests (meetup.com), and initiate relationships (match.com) have all been remarkably successful. But what about sharing local news? Success with local news has been less pervasive and straightforward. Arguably, this is because existing solutions have not yet fully uncovered the true needs and barriers to sharing local news.

Another method for determining what these needs and barriers might be is to monitor online tools that excel at supporting a breadth of communications. Within these tools, we might find clusters of people who share geographic proximity and are actively communicating. Identifying patterns in communications or locations here will reveal which local needs may be benefiting most from the reduced friction of online communication.

Interestingly, most social networking tools provide little of this local communication. Both Linkedin and Facebook, for example, seem to excel at connecting out of touch and geographically disparate individuals. Things have started to shift, however, with the introduction of the short messaging system, Twitter. With Twitter, people are starting to connect with one another simply because they are nearby. Twitter seems different in this regard, and understanding how Twitter is different might just be the key to understanding where frictionless local communication holds the most promise.

Twitter saw its first big explosion in usage during the 2007 SXSW festival in Austin, TX. This was in large part due to the attendee’s unresolved need to connect with others at the conference. Ironic as this may seem, as you move around an event such as a conference, you become a mostly passive recipient of information, cut off from explicitly sharing the experience with others. Communication needs at large events like this range from broadcast heckles to simple queries around where your friends are, what events are attendance-worthy, and who to get to know. In my own experience, this proximity-effect of Twitter carries over into day-to-day situations as well - it becomes valuable to follow someone simply because they live near you. But why?

I believe one answer lies in the immediacy of the information that is shared. Specifically, it is surprisingly difficult to share information about what's going on right now amongst people near one other. As with SXSW, local twitter messages (tweets) are most valuable when they contain information about what is happening right now – often something that might affect me because of our relative proximity. For example, I might monitor the tweets from those I follow locally to know where they are or where they’re going so that I can (presumably) join them. It’s valuable to find out about something as it happens. I can always visit a traditional news source if I need to seek out a specific piece of information or learn of important happenings after the fact, but who’s going to let me know of something important going on right now? It's this active nature of twitter, filtered by real people, providing immediately sourced, proximal information that makes it so valuable. Nothing seems to match twitter for a real-time assessment of what I need to know about that’s going on near me.

Perhaps Twitter points to only one unresolved need – the need for immediate, proximal information, but I believe this need will blossom into a more significant source of local news and take different forms as it more seamlessly encourages useful sharing.

Frankly, I'm surprised it took so long to happen. Or maybe I just didn't notice it happening much until now. When google pioneered contextual advertising, I assumed that the rest of the world would follow in spades. We'd be getting emailed, nudged, banner-added and text messaged whenever we displayed online intention or contextual curiosity. There is a world of nuance between blatantly unsolicited email spam and "relevant online communications," and I assumed that businesses would rush in to fill this gap. But I really haven't seen it that much. Until now.
 
Enter the Twitter Hawks. Businesses that hover on top of Twitter search terms and then @ you if you mention something relevant to their business. For example, I just got an @ message from an airport shuttle service when they saw me use the name of an airport in my tweet. Obviously, they're monitoring the public feed using Twitter Search or the Search API and replying publicly to tweets that mention airport travel in their business service range. But is this spam? Well, I suppose not the traditional type, but it's definitely unwelcome when my @ stream is filled with unsolicited business messages from orgs - no matter how "well intentioned" who are hovering over my communications.
 
Like any good enabling technology, people see opportunity and rush in to explore, address, solve, and experiment. I'm not surprised that people are exploring this gap, I'm just surprised it took so long.

Last week I posted a mini-app that helps find popular twitter users near you. Simply enter a location, and Twitterstars will search regional tweets and return the top five most-followed Twitter users.

Your Location (City, State):

I got some good sleuthing and feedback from the genius behind lolcode, and have subsequently made some updates and learned enough to provide some caveats. Tips & Caveats:

  • Since this app hits multiple web services, expect a little bit of waiting time as the data is retrieved.
  • If the page returns empty, this is likely because Twitter is struggling under server load or is rejecting API requests from Yahoo! Pipes (known issue)
  • I've locked the radius of search to 15 miles, which in most cases encircles users who put the city name you've searched for in their profile (twitter search API uses LAT and LONG coordinates). I have discovered some examples where the search API stumbles on stated locations, however
  • The Twitter search API returns a maximum of 100 tweets and must analyze users from within that collection. This means that if a popular user has not tweeted within the time window determined by the 100 most recent tweets (sometimes as little as a few minutes in the case of, say, NY, NY), then they will not be included in the search results. Try multiple times during the day to get different results.
  • The Twitter Search API is notorious for its latency. If you're trying to catch a very recent tweet in the result set, you generally won't be successful.
  • Pipes requests in rapid succession will return cached data, so it's not enough to simply hit refresh on the results page (sorry). Wait a few minutes and try again, or hack the URL to change the search radius or LAT/LONG, etc.

If you find this mini-application useful, please let me know. Suggestions for modifications and improvements are always welcome.

[Note: I've posted a Twitterstars update]

Finding and connecting with local social media 'superstars' can be a valuable short-cut for anyone trying to ramp up quickly in online social environments. These enthusiasts are knowledgeable about social media tools, are highly-connected, and understand well how to succeed in the online social environment.

But how do you find the local social media superstars? Today, many of these individuals use Twitter. The "Local Twitterstars" mini-application below takes any US geographic search area that you provide and returns a feed of the top five most followed individuals on Twitter who have been recently active in the region. Below is a more detailed explanation of how I built this mini-application. I also posted an update here.

Location (City, State):

Radius (in Miles):


This mini-application uses the Twitter Search API, the Twitter REST API, Yahoo! Pipes, and some simple HTML.

  1. The simple HTML form above constructs a server GET request through both hidden and user-populated form fields.
  2. This constructed URL queries a custom-built Yahoo! Pipe that takes the location from the URL and converts it to LAT-LONG coordinates.
  3. A Twitter search API query is then constructed by the Pipe using the LAT-LONG and radius data, returning the 100 most recent tweets in this region. Depending on your search area, this could include only very recent tweets or could span a much longer time period. Twitter has some internal smarts around matching the coordinates to include a variety of data that users put into the location field of their profile, including towns, zip codes, iPhone GPS coordinates, etc.
  4. The Pipe then takes all the tweets and constructs a series of queries to the Twitter REST API, pulling back user profile data from each user behind the tweets.
  5. After removing duplicates, the Pipe selects the top five most followed users in the list and builds an RSS feed presenting the username, a link to their twitter account, and the current number of followers they have.

NOTE: If the feed request is empty, try changing your search criteria. It's also quite possible that Twitter is struggling to handle load and won't fulfill the API requests.

If you find this mini-application useful, please let me know. Suggestions for modifications and improvements are always welcome.

Update 6/29/09: Thanks for all the coverage!

NPRbackstory is an experimental web mashup that I created to dig through the NPR archives and unearth the Public Radio backstory on currently trending topics. This "application" is currently running in Beta as a Twitter account. To use the application, you need to follow NPRbackstory in Twitter. I welcome any feedback on this idea in the comments section below.

I should note that I built this as a personal project to play with the public version of the NPR API. At the time I was not an NPR employee (I am now), so this experiment doesn't reflect the strategy of NPR or even have their official support. I'm grateful for the coverage that Harvard's Neiman Journalism Lab and others have given this project and to NPR for not pulling my API key ;-)

Follow the NPRbackstory Twitter account

My favorite public radio segments provide thought provoking backstories on current news items. It might be a Terry Gross interview from a few years back of a famous person that just passed away, or a cultural sketch of an unfamiliar country that had a coup d'état this morning.

One of great things about the backstory approach is that it provides context and lends meaning to a current event. The backstory brings the listener up to date on a trendy news item without wallowing in the sensationalist details often found in mainstream news coverage.

In an attempt to bring this great idea to the web, here is a simple web application that generates an RSS feed of NPR online content. Rather than just a feed of NPR news, the NPRbackstory application tries to intelligently match fast-rising, trendy search terms to existing content on NPR.org. This goes beyond news coverage to include media from NPR blogs, interviews, NPR music, program content, podcasts, and station pieces (all thanks to the NPR API).

Below is the latest few items from the NPRbackstory Twitter feed. The keyword in parentheses is the fast-rising search term. The headline is the story, blog post, audio segment, or media from npr.org.


I'm encouraged by initial results from NPRbackstory. Here are some interesting "backstories" from the first few hours:

(ryan seacrest) Apparently, Ryan was recently bitten by a shark, resulting in a surge of web searches on his name. The backstory? A "Morning Edition" audio piece and write-up from September 2007 on Ryan entitled, "Hosting a TV show, how hard can it be?"

(jerry lee) Jerry Lee Lewis just detained for allegedly trying to take a gun on a plane. NPRbackstory returns his downloadable NPR Music "Song of the Day" from 2006.

(medical information) This web trend spiked because of a medical record leak of up to 200,000 people in Georgia. The backstory turns out to be a bit eerie: A "Morning Edition" segment on the trade-offs of online medical records from April of 2008.

The NPRbackstory "Application" was created by Keith Hopper using the NPR API, Dapper, Twitterfeed, Feedburner, and Yahoo! Pipes. If anyone is interested in the details, let me know and I can post them here. And why not follow @khopper on Twitter to see what else I might be up to?
Update 7/11: Since I posted this, the failwhale phenomenon has gotten beautifully out of hand. See my original post on this.

Much has been said about the remix, but riffing on ideas - specifically internet memes, is a slightly different beast. An original idea that resonates might just inspire someone to put a spin on it, extending or enhancing the idea. This is perhaps more common than is generally recognized, and I would argue, a growing trend.

For example, I was recently directed to a clever image that poked fun at Twitter culture on a day that Twitter was suffering performance issues. This image resonated with me because I TOO was affected by these issues and was inspired to attach my own meaning and create a different image that poked fun. This, in turn, inspired a friend to create more, clever interpretations of the idea...

(From Twitter)

 

(from Mykl Roventine)

 

(From Keith Hopper)

 

(from Andy Carvin)

This is only one example of an expressive idea train, where each of us saw different meaning and chose to share that meaning in a slightly different way. Based on how a specific idea might inspire you (and towards what ends), modification and republishing of a meme might manifest as a remix, knockoff, spinout, or analog of the original idea, described as follows:

Remix: Taking a single idea and modifying the orginal content. For example, you might take a funny image and give it a soundtrack, or mash it up with a video, making it funny in a new context.

Knockoff: Same idea, different name. Generally done by someone who perhaps wants to suggest they originated it.

Spinout: Different idea, but with a common source of inspiration, such as a topic - like different jokes based on the same high-profile cultural event.

Analog: New content based on the same core concept - often in a different context, e.g. LOLcode as a derivative of LOLcats.

Update 7/11: Since I posted this, the failwhale phenomenon has gotten beautifully out of hand. See my follow-up post to this.

Some of you Twitter fans may have noticed that Twitter couldn't handle the load today. Here was the pleasant image that was provided on the site as scalability suffered: I couldn't help but think this image is a little misleading. I don't know about you, but I do not feel as though I am being flown through the air, gently carried by a fleet of doves, eyes closed in near-ecstasy. Here is, perhaps, an alternative notification that more accurately communicates my feelings: (inspired by another alternative here)

Tagged:

(as found on TweetStats)

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