- Hyundia Replacing Cigarette Lighters with USB Ports (Quartz) — sign of the times. (via Julie Starr)
- Freeseer — free, open source, cross-platform application that captures or streams your desktop—designed for capturing presentations. Would you like freedom with your screencast?
- Amazon Redshift: What You Need to Know — good write-up of experience using Amazon’s column database.
- GroupTweet — Allow any number of contributors to Tweet from a group account safely and securely. (via Jenny Magiera)
ENTRIES TAGGED "Twitter"
USB in Cars, Capture Presentations, Amazon Redshift, and Polytweeting
In some key use cases a random sample of tweets can capture important patterns and trends
Researchers and companies who need social media data frequently turn to Twitter’s API to access a random sample of tweets. Those who can afford to pay (or have been granted access) use the more comprehensive feed (the firehose) available through a group of certified data resellers. Does the random sample of tweets allow you to capture important patterns and trends? I recently came across two papers that shed light on this question.
Systematic comparison of the Streaming API and the Firehose
A recent paper from ASU and CMU compared data from the streaming API and the firehose, and found mixed results. Let me highlight two cases addressed in the paper: identifying popular hashtags and influential users.
Of interest to many users is the list of top hashtags. Can one identify the “top n” hastags using data made available throughthe streaming API? The graph below is a comparison of the streaming API to the firehose: n (as in “top n” hashtags) vs. correlation (Kendall’s Tau). The researchers found that the streaming API provides a good list of hashtags when n is large, but is misleading for small n.
Geeky Primer, Visible CSS, Remote Working, and Raspberry Pi Sentiment Server
- My Little Geek — children’s primer with a geeky bent. A is for Android, B is for Binary, C is for Caffeine …. They have a Kickstarter for two sequels: numbers and shapes.
- Visible CSS Rules — Enter a url to see how the css rules interact with that page.
- How to Work Remotely — none of this is rocket science, it’s all true and things we had to learn the hard way.
- Raspberry Pi Twitter Sentiment Server — step-by-step guide, and github repo for the lazy. (via Jason Bell)
iOS Package Manager, Designed Satire, API Fragility, and Retweeting WWI
- Alcatraz — package manager for iOS. (via Hacker News)
- Scarfolk Council — clever satire, the concept being a UK town stuck in 1979. Tupperware urns, “put old people down at birth”. The 1979 look is gorgeous. (via BoingBoing)
- Stop Designing Fragile Web APIs — It is possible to design your API in a manner that reduces its fragility and increases its resilience to change. The key is to design your API around its intent. In the SOA world, this is also referred to as business-orientation.
- @life100yearsago (Twitter) — account that tweets out fragments of New Zealand journals and newspapers and similar historic documents, as part of celebrating the surprising and the commonplace during WWI. My favourite so far: “Wizard” stones aeroplane. (via NDF)
Reuters' Connected China, accessing Pew's datasets, Simon Rogers' move to Twitter, data privacy solutions, and Intel's shift away from chips.
Reuters launches Connected China, Pew instructs on downloading its data, and Twitter gets a data editor
Yue Qiu and Wenxiong Zhang took a look this week at a data journalism effort by Reuters, the Connected China visualization application. Qiu and Zhang report that “[o]ver the course of about 18 months, a dozen bilingual reporters based in Hong Kong dug into government websites, government reports, policy papers, Mainland major publications, English news reporting, academic texts, and think-tank reports to build up the database.”
Twitter has hired Guardian Data editor Simon Rogers as its first data editor.
Twitter has hired its first data editor. Simon Rogers, one of the leading practitioners of data journalism in the world, will join Twitter in May. He will be moving his family from London to San Francisco and applying his skills to telling data-driven stories using tweets. James Ball will replace him as the Guardian’s new data editor.
As a data editor, will Rogers keep editing and producing something that we’ll recognize as journalism? Will his work at Twitter be different than what Google Think or Facebook Stories delivers? Different in terms of how he tells stories with data? Or is the difference that Twitter has a lot more revenue coming in or sees data-driven storytelling as core to driving more business? (Rogers wouldn’t comment on those counts.)