ENTRIES TAGGED "writing"

Four short links: 18 April 2014

Four short links: 18 April 2014

Interview Tips, Data of Any Size, Science Writing, and Instrumented Javascript

  1. 16 Interviewing Tips for User Studies — these apply to many situations beyond user interviews, too.
  2. The Backlash Against Big Data contd. (Mike Loukides) — Learn to be a data skeptic. That doesn’t mean becoming skeptical about the value of data; it means asking the hard questions that anyone claiming to be a data scientist should ask. Think carefully about the questions you’re asking, the data you have to work with, and the results that you’re getting. And learn that data is about enabling intelligent discussions, not about turning a crank and having the right answer pop out.
  3. The Science of Science Writing (American Scientist) — also applicable beyond the specific field for which it was written.
  4. earhornEarhorn instruments your JavaScript and shows you a detailed, reversible, line-by-line log of JavaScript execution, sort of like console.log’s crazy uncle.
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Four short links: 10 April 2014

Four short links: 10 April 2014

Rise of the Patent Troll, Farm Data, The Block Chain, and Better Writing

  1. Rise of the Patent Troll: Everything is a Remix (YouTube) — primer on patent trolls, in language anyone can follow. Part of the fixpatents.org campaign. (via BoingBoing)
  2. Petabytes of Field Data (GigaOm) — Farm Intelligence using sensors and computer vision to generate data for better farm decision making.
  3. Bullish on Blockchain (Fred Wilson) — our 2014 fund will be built during the blockchain cycle. “The blockchain” is bitcoin’s distributed consensus system, interesting because it’s the return of p2p from the Chasm of Ridicule or whatever the Gartner Trite Cycle calls the time between first investment bubble and second investment bubble under another name.
  4. Hemingway — online writing tool to help you make your writing clear and direct. (via Nina Simon)
Comments: 2
Four short links: 25 January 2013

Four short links: 25 January 2013

Bio-Writing, Internet Fame, Obama's Tech, and Precog Software

  1. How to Write a Good Bio (Scott Berkun) — something we all have to do, and rarely do well the first time. Excellent advice.
  2. Scumbag Steve’s Advice for Annoying Facebook GirlSome people can’t distinguish the internet from real life. There are people who refuse to believe my name isn’t Steve and that I am not really the scumbag (well not all the time, that is). Just remember who you are. And that you know you’re a decent kid. Blake (the guy whose image was adopted as “Scumbag Steve” by meme-makers) was 21 when he wrote that, and it remains the best advice for anyone dealing with sudden visibility in the public eye.
  3. The Battle for Obama’s Tech (The Verge) — same old story: the software that got Obama elected won’t be released. Instead it’ll atrophy and have to be rewritten in four years’ time. How do I know this? The morons at the Democratic Party did it with Kerry’s run and again for Obama’s first campaign. It’s a choice the OFA developers warn could not only squander the digital advantage the Democrats now hold, but also severely impact their ability to recruit top tech talent in the future.
  4. Precog Software (Wired) — researchers assembled a dataset of more than 60,000 crimes, including homicides, then wrote an algorithm to find the people behind the crimes who were more likely to commit murder when paroled or put on probation. Berk claims the software could identify eight future murderers out of 100. The software parses about two dozen variables, including criminal record and geographic location. The type of crime and the age at which it was committed, however, turned out to be two of the most predictive variables. [...] The software aims to replace the judgments parole officers already make based on a parolee’s criminal record and is currently being used in Baltimore and Philadelphia. I look forward to the study comparing human judgement from parole officers against algorithmic judgement.
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Mark Twain on influence

A letter asking for an introduction meets a meditation on self-reliance.

In 1905 Mark Twain wrestled with the sort of request that many readers here have undoubtedly encountered: a new writer with the most tenuous of connections (her uncle was briefly a neighbor in a Nevada mining town) asks Twain to use his influence to get  her manuscript published.

It never hurts to carry an introduction from a well-regarded intermediary, as long as your introducer can actually speak to the quality of your work. I think of Twain’s anguished reply every time I’m asked to recommend someone or something I don’t know — or am tempted to ask the same favor of someone else.

Twain’s message is ultimately optimistic: don’t simply try to accumulate influence. Instead, come up with a good idea and sell it on its merits. The world will listen.

The full text of Twain’s essay is below, via Project Gutenberg. Read more…

Comments: 7

Saving publishing, one tweet at a time

Helping both readers and writers look good on social media.

Traffic comes to online publishers in two ways: search and social. Because of this, writing for the tweet is a new discipline every writer and editor must learn. You’re not ready to publish until you find the well crafted headline that fits in 100 characters or so, and pick an image that looks great shared at thumbnail size on Facebook and LinkedIn.

But what of us, the intelligent reader? Nobody wants to look like a retweet bot for publishers. The retweet allows us no space to say why we ourselves liked an article.

Those of us with time to dedicate are familiar with crafting our own awkward commentaries: “gr8 insight in2 state of mob,” “saw ths tlk last Feb,” “govt fell off fiscal clf”. Most of the time it’s easier just to bookmark, or hit “read later,” and not put in the effort to share.

Rescue is at hand. The writer and programmer Paul Ford has created a bookmarklet, entitled Save Publishing. On activating the bookmarklet while viewing an article you wish to share, it highlights and makes clickable all the tweetable phrases from the page. Read more…

Comments: 3
Four short links: 26 December 2011

Four short links: 26 December 2011

Text Analysis Bundle, Scala Probabilistic Modeling, Game Analytics, and Encouraging Writing

  1. Pattern — a BSD-licensed bundle of Python tools for data retrieval, text analysis, and data visualization. If you were going to get started with accessible data (Twitter, Google), the fundamentals of analysis (entity extraction, clustering), and some basic visualizations of graph relationships, you could do a lot worse than to start here.
  2. Factorie (Google Code) — Apache-licensed Scala library for a probabilistic modeling technique successfully applied to [...] named entity recognition, entity resolution, relation extraction, parsing, schema matching, ontology alignment, latent-variable generative models, including latent Dirichlet allocation. The state-of-the-art big data analysis tools are increasingly open source, presumably because the value lies in their application not in their existence. This is good news for everyone with a new application.
  3. Playtomic — analytics as a service for gaming companies to learn what players actually do in their games. There aren’t many fields untouched by analytics.
  4. Write or Die — iPad app for writers where, if you don’t keep writing, it begins to delete what you wrote earlier. Good for production to deadlines; reflective editing and deep thought not included.
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Four short links: 10 November 2011

Four short links: 10 November 2011

Access Over Ownership, Retro Programming, Replaying Writing, and Wearable Sensors

  1. Steve Case and His Companies (The Atlantic) — Maybe you see three random ideas. Case and his team saw three bets that paid off thanks to a new Web economy that promotes power in numbers and access over ownership. “Access over ownership” is a phrase that resonated. (via Walt Mossberg)
  2. Back to the Future — teaching kids to program by giving them microcomputers from the 80s. I sat my kids down with a C64 emulator and an Usborne book to work through some BASIC examples. It’s not a panacea, but it solves a lot of bootstrapping problems with teaching kids to program.
  3. Replaying Writing an Essay — Paul Graham wrote an essay using one of his funded startups, Stypi, and then had them hack it so you could replay the development with the feature that everything that was later deleted is highlighted yellow as it’s written. The result is fascinating to watch. I would like my text editor to show me what I need to delete ;)
  4. Jawbone Live Up — wristband that sync with iPhone. Interesting wearable product, tied into ability to gather data on ourselves. The product looks physically nice, but the quantified self user experience needs the same experience and smoothness. Intrusive (“and now I’m quantifying myself!”) limits the audience to nerds or the VERY motivated.
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How I automated my writing career

How I automated my writing career

A former author uses data and software to take the tedium out of some kinds of writing.

You scale content businesses by increasing the number of people who create the content … or so conventional wisdom says. Learn how a former author is using software to simulate and expand human-quality writing.

Comments: 18
Four short links: 3 February 2011

Four short links: 3 February 2011

Commandline for Story, Dystopic Predictions, Studying Failures, and Two Great Tastes

  1. Curveship — a new interactive fiction system that can tell the same story in many different ways. Check out the examples on the home page. Important because interactive fiction and the command-lines of our lives are inextricably intertwined.
  2. Egypt’s Revolution: Coming to an Economy Near You (Umair Haque) — more dystopic prediction, but this phrase rings true: The lesson: You can’t steal the future forever — and, in a hyperconnected world, you probably can’t steal as much of it for as long.
  3. Why Startups Fail — failure is a more instructive teacher than success, so simply studying successful startups isn’t enough. (via Hacker News)
  4. Computer Science and Philosophy — Oxford is offering a program studying CS and Philosophy together. the two disciplines share a broad focus on the representation of information and rational inference, embracing common interests in algorithms, cognition, intelligence, language, models, proof, and verification. Computer Scientists need to be able to reflect critically and philosophically about these, as they push forward into novel domains. Philosophers need to understand them within a world increasingly shaped by computer technology, in which a whole new range of enquiry has opened up, from the philosophy of AI, artificial life and computation, to the ethics of privacy and intellectual property, to the epistemology of computer models (e.g. of global warming). I wish every CS student had taken a course in ethics.
Comment: 1
Four short links: 9 September 2010

Four short links: 9 September 2010

Thumb Drives and the Cloud, FCC APIs, Mining on GFS, Check Your Prose with Scribe

  1. CloudUSBa USB key containing your operating environment and your data + a protected folder so nobody can access you data, even if you lost the key + a backup program which keeps a copy of your data on an online disk, with double password protection. (via ferrouswheel on Twitter)
  2. FCC APIs — for spectrum licenses, consumer broadband tests, census block search, and more. (via rjweeks70 on Twitter)
  3. Sibyl: A system for large scale machine learning (PDF) — paper from Google researchers on how to build machine learning on top of a system designed for batch processing. (via Greg Linden)
  4. The Surprisingness of What We Say About Ourselves (BERG London) — I made a chart of word-by-word surprisingness: given the statement so far, could Scribe predict what would come next?
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