Talking to Twitter
Integrating into Your Application
As you can see, working with Twitter is surprisingly easy. The startup time for connecting to Twitter can take a little bit of time—up to two seconds, in my experience—but tweeting and querying Twitter take very little time. It's obvious, as a consumer of the API, that they have worked hard to make it execute as quickly as possible. This is a lesson to all of us who create APIs. We all know that Web pages should load quickly, and that slow load times can discourage people from staying on a site.
API calls typically are embedded within another application, meaning that if the API call takes time, the application itself will feel sluggish. As a result, a slow API call will lead to slow responses from the API clients—and may discourage people from using your API.
But where would you use such API calls? Why would you want to use Twitter on your site?
One simple use of the Twitter API would be to display a user's most recent tweets. For example, if your company (or you personally) use Twitter to send messages about what you are doing, you can see that it would be fairly easy to include those tweets in a Web page. Using an MVC system, such as Rails, you simply would grab the tweets (with the "user_timeline" method, as shown above), and stick the results on your home page. Now your home page provides another view to your Twitter feed, re-enforcing its importance and usage to your company.
I have been doing something slightly different. As I mentioned previously, I have begun to use Twitter to log public activity in the application I've developed for my dissertation. Every time a new user joins, new content is posted or someone adds a posting to a discussion forum, I send a new tweet on the subject. In and of itself, this doesn't do very much; Twitter is full of text and URLs. But I have certainly found by ensuring that my tweets are followed and seen by a large number of people, I have increased the number of users coming to my site.
In other words, by tweeting about activity on my site, I have given my site additional exposure to the world. Moreover, people who really want to see what my application is doing can follow the link in their Twitter feed and follow along.
By adding a #NetLogo hashtag to my tweets, I also have made it possible, and even easy, for my tweets (and thus my site) to be found and identified by people searching Twitter for mentions of our modeling environment. The fact that Google indexes tweets increases my site's visibility on-line among people who are searching for modeling-related sites.
The net effect has been rather huge. Within two weeks of starting to use Twitter to announce updates on my site, the number of people coming to visit has increased dramatically. Not coincidentally, my site's ranking in Google has improved noticeably.
Now, if this were a commercial site, rather than a free infrastructure for collaborative modeling, I would want to check a second thing, namely the "conversion rate"—that is, how many people who came to my site also became paying customers. But for my small, educational site, it has been fascinating to see what a difference tweeting made.
And what did I do? Truth be told, not much. I set up things such that
a new tweet would be sent, using the "update" method demonstrated
above, every time a new model version, forum posting or person was
added to the system. Because of the relatively low latency on the
"update" method, I even do this inline on an
within Rails, rather than queueing it in a background job.
The biggest technical challenge I have faced so far in all of this is the issue of duplicate tweets. When I first set up the Twitter feed, I defined the tweet for an additional discussion forum post to be:
Reuven Lerner has added a comment about the Foobar model!
The problem with this style of tweet is that it quickly can lead to duplicates—and thus errors from within the application. As a result, I have made sure that every tweet has a unique number in it somewhere, typically counting how many similar objects already have been created. For example:
Reuven Lerner wrote the 5th comment about the Foobar model!
The above ensures—assuming that user and model names are unique—that there cannot be duplicates, thus avoiding the problem.
Beyond the advantages for users, SEO and people interested in following my work, I also have found it to be enormously satisfying to see tweets come out even when I'm not aware of it. It's similar in some ways to seeing my children's creative output, but (obviously) less emotionally charged.
Adding automatic tweets to a Web application is easy to do and can have significant benefits. For your users, it gives them a way to follow what is happening in your application without needing to visit the site or use an RSS reader. For your site, automatic tweets will help bring in new visitors, improve SEO and generally improve your project's visibility.
Twitter, of course, is at http://twitter.com. The developer and API documentation is at http://dev.twitter.com. The Ruby gem for Twitter, which apparently has been downloaded more than one million times (!), is at http://sferik.github.io/twitter.
Reuven M. Lerner, Linux Journal Senior Columnist, a longtime Web developer, consultant and trainer, is completing his PhD in learning sciences at Northwestern University.
Pick up any e-commerce web or mobile app today, and you’ll be holding a mashup of interconnected applications and services from a variety of different providers. For instance, when you connect to Amazon’s e-commerce app, cookies, tags and pixels that are monitored by solutions like Exact Target, BazaarVoice, Bing, Shopzilla, Liveramp and Google Tag Manager track every action you take. You’re presented with special offers and coupons based on your viewing and buying patterns. If you find something you want for your birthday, a third party manages your wish list, which you can share through multiple social- media outlets or email to a friend. When you select something to buy, you find yourself presented with similar items as kind suggestions. And when you finally check out, you’re offered the ability to pay with promo codes, gifts cards, PayPal or a variety of credit cards.Get the Guide
|Be Kind, Buffer!||Apr 26, 2017|
|Preparing Data for Machine Learning||Apr 25, 2017|
|openHAB||Apr 24, 2017|
|Omesh Tickoo and Ravi Iyer's Making Sense of Sensors (Apress)||Apr 21, 2017|
|Low Power Wireless: 6LoWPAN, IEEE802.15.4 and the Raspberry Pi||Apr 20, 2017|
|CodeLathe's Tonido Personal Cloud||Apr 19, 2017|
- Preparing Data for Machine Learning
- Be Kind, Buffer!
- Teradici's Cloud Access Platform: "Plug & Play" Cloud for the Enterprise
- The Weather Outside Is Frightful (Or Is It?)
- Simple Server Hardening
- Understanding Firewalld in Multi-Zone Configurations
- Bash Shell Script: Building a Better March Madness Bracket
- Server Technology's HDOT Alt-Phase Switched POPS PDU
- Gordon H. Williams' Making Things Smart (Maker Media, Inc.)