Who Knew First: Steve Jobs or Aron Pinson?

While Steve Jobs’ resignation yesterday had investors anxiously watching how $AAPL fared in trading, we at Gnip were having fun watching a different ticker- the realtime Twitter feed.

As you can see from the graph below (these represent the number of “Steve Jobs” mentions per minute*), Twitter showed an incredible spike almost immediately. Apple-specific activity peaked 11 minutes after the news broke, showing how quickly the word spread. Honors for first tweet go to @AronPinson, who must have some blazing fast typing skills.

Once again, it’s incredible to see how social media is quickly becoming a trusted means of accessing and delivering realtime information.

*For more details on how we conducted this search across the millions of real-time tweets we have access to, contact us!

Gnip. The Story Behind the Name

Have you ever thought “Gnip”. . . well that is a strange name for a company, what does it mean? As one of the newest members of the Gnip team I found myself thinking that very same thing. And as I began telling my friends about this amazing new start-up that I was going to be working for in Boulder, Colorado they too began to inquire as to the meaning behind the name.

Gnip, pronounced (guh’nip), got its name from the very heart of what we do, realtime social media data collection and delivery. So let’s dive in to . . .

Data Collection 101

There are two general methods for data collection, pull technology and push technology. Pull technology is best described as a data transfer in which the request is initiated by the data consumer and responded to by the data publisher’s server. In contrast, push technology refers to the request being initiated by the data publisher’s server and sent to the data consumer.

So why does this matter . . .

Well most social media publishers use the pull method. This means that the data consumer’s system must constantly go out and “ping” the data publisher’s server asking, “do you have any new data now?” . . . “how about now?” . . . “and now?” And this can cause a few issues:

  1. Deduplication – If you ping the social media server one second and then ping it again a second later and there were no new results, you will receive the same results you got one second ago. This would then require deduplication of the data.
  2. Rate Limiting – every social media data publisher’s server out there sets different rate limits, a limit used to control the number of times you can ping a server in a given time frame. These rate limits are constantly changing and typically don’t get published. As such, if your server is set to ping the publisher’s server above the rate limit, it could potentially result in complete shut down of your data collection, leaving you to determine why the connection is broken (Is it the API . . . Is it the rate limit . . . What is the rate limit)?

So as you can see, pull technology can be a tricky beast.

Enter Gnip

Gnip sought to provide our customers with the option: to receive data in either the push model or the pull model, regardless of the native delivery from the data publisher’s server. In other words we wanted to reverse the “ping” process for our customers. Hence, we reversed the word “ping” to get the name Gnip. And there you have it, the story behind the name!

Social Media in Natural Disasters

Gnip is located in Boulder, CO, and we’re unfortunately experiencing a spate of serious wildfires as we wind Summer down. Social media has been a crucial source of information for the community here over the past week as we have collectively Tweeted, Flickred, YouTubed and Facebooked our experiences. Mashups depicting the fires and associated social media quickly started emerging after the fires started. VisionLink (a Gnip customer) produced the most useful aggregated map of official boundary & placemark data, coupled with social media delivered by Gnip (click the “Feeds” section along the left-side to toggle social media); screenshot below.

Visionlink Gnip Social Media Map

With Gnip, they started displaying geo-located Tweets, then added Flickr photos with the flip of a switch. No new messy integrations that required learning a new API with all of it’s rate limiting, formatting, and delivery protocol nuances. Simple selection of data sources they deemed relevant to informing a community reacting, real-time, to a disaster.

It was great to see a firm focus on their core value proposition (official disaster relief data), and quickly integrate relevant social media without all the fuss.

Our thoughts are with everyone who was impacted by the fires.