SRCCON 2018 session pitch: New templates for presenting information

Here’s my pitch for this June’s SRCCON conference:

Dumplings, defamiliarization and how to create new templates for presenting information

Taeyoon Choi cooks dumplings to demonstrate how a CPU works. To teach creative applications of technology, he takes a fun and tactile approach in explaining a complex subject. We also aim to explain complicated topics in news, but constraints of time, money and staffing can make that difficult. Instead we often use formats like graphic templates or explainer stories. But what we if we created new templates that didn’t just simplify our subject matter, but made it engaging in a way that spurs exploration and understanding?

We’ll share examples like the CPU dumplings and ideas from art history like defamiliarization. Then we’ll break into groups to devise and compile new approaches to presenting information inspired by the discussion.

Initial inspiration came at NICAR18 in Chicago during a conversation with Allison McCartney (stay tuned for a future pitch we’re planning). A day before we chatted, I attended session on Data Viz in the Upside, which made me think of how the concept of defamiliarization could inform how journalists present information. Here are the slides from that session:

Additional inspiration for the SRCCON pitch came from this video:

Coincidentally, a few weeks after watching the dumpling video, I happened to watch a talk by John Maeda. A couple minutes in, he shows a clip from the 90s of a similar live-action explanation of how a computer works:

Overall, my favorite line was:

“You know, when people say, ‘I don’t get art. I don’t get it at all.’ That means art is working, you know?”

In news, of course, we want to help people “get it.” So, if the session is picked, we’ll try and adapt some techniques from art to improve understanding of the world.

 

 

 

 

 

 

 

 

SRCCON 2016 proposals: building a data community and embracing the arts

Since I’ll be in the country this time around, I’m hoping to attend my first SRCCON this summer in Portland. Here’s a brief description from the organizers, Knight-Mozilla OpenNews:

SRCCON is a hands-on conference focused on the practical challenges news technology and data teams encounter every day. We work to make it an inclusive and welcoming event where people can feel comfortable digging into complex problems.

Here are the pitches:

Continue reading SRCCON 2016 proposals: building a data community and embracing the arts

Video and updates from ONA15 session: Whose Idea of the Future Is This?

I organized a session at this year’s Online News Association 2015 conference in Los Angeles with an awesome group of speakers:

We’ve assembled a group of experts on futurism to look at predictions and possibilities for how our society is changing, and help rethink our approach to media, technology and our communities.

Here’s the session page. Here’s the Storify:

Continue reading Video and updates from ONA15 session: Whose Idea of the Future Is This?

Highlights from #cj2014 opening keynote: Jon Kleinberg

I’m following the Computation + Journalism 2014 symposium via the hashtag and livestream. Below are some highlights I collected from the opening keynote.

#cj2014: Tracing the Flow of On-Line Information through Networks and Text

Keynote by Jon Kleinberg at 2014 Computation + Journalism symposium at Columbia University

  1. Event page:
  2. Highlights from the keynote (in chronological order):
  3. Keynote by Jon Kleinberg of Cornell: metaphors of information travelling online include the library and the crowd #cj2014
  4. #Information travels on-line via #library (pages, links, association) & crowd (memes, contagion) | #data #CJ2014
  5. Jon Kleinberg opens #CJ2014 with a ref to the classic essay As We May Think.  http://j.mp/ZPWaO1 
  6. Jon Kleinberg, speaking right now at #cj2014, did some really cool work tracking chain letters online in 2008  http://www.pnas.org/content/105/12/4633.full 
  7. We can track the flow of information temporally, structurally, and in terms of content, says Jon Kleinberg #cj2014
  8. But are crowd & library metaphors dual: people trailblazing through documents or documents transmitted through networks of people? #cj2014
  9. It’s easier for algorithms to track items (quotes, photos, phrases) than stories. Q: Does that encourage pack journalism? #CJ2014
  10. Tracking stories through networks reveals difficulties eg., natural language. But can track quotes to show news cycles #CJ2014
  11. Kleinberg explains tracking essential elements of a story (like phrases) as they move through networks. #cj2014 http://t.co/V1fiFZWUBS

    Kleinberg explains tracking essential elements of a story (like phrases) as they move through networks. #cj2014 pic.twitter.com/V1fiFZWUBS
  12. Half of all reshares on FB happen in large cascades (>500) | #paradox #viral #CJ2014
  13. Basic question: how to predict what content will be shared widely? Or, are cascades unpredictable? #cj2014 http://t.co/Q7dCleEkXH

    Basic question: how to predict what content will be shared widely? Or, are cascades unpredictable? #cj2014 pic.twitter.com/Q7dCleEkXH
  14. #cj2014 Is virality predictable? You as poster rarely experience it w your content, but you as consumer see it often http://t.co/IEgOmZtWIv

    #cj2014 Is virality predictable? You as poster rarely experience it w your content, but you as consumer see it often pic.twitter.com/IEgOmZtWIv
  15. One solution: reframe question as tracking rather than snapshot instant: what are the chances of this being shared further? #cj2014
  16. On whether something “goes viral”: “An important moment in a cascade is the moment it escapes the neighborhood of the root.” #cj2014
  17. Temporal features most powerful in predicting resharing of photo memes #CJ2014 http://t.co/3ZKFHIzO7Y

    Temporal features most powerful in predicting resharing of photo memes #CJ2014 pic.twitter.com/3ZKFHIzO7Y
  18. My thoughts are on how narratives or stories in news, eg images of ‘typical’ migrants, circulate and are widely diffused #cj2014
  19. Troubling finding here seems to be that actual content has less impact on how likely something is to go viral #cj2014 http://t.co/lver1zx14e

    Troubling finding here seems to be that actual content has less impact on how likely something is to go viral #cj2014 pic.twitter.com/lver1zx14e
  20. Research to understand discussion and comment threads - #cj2014 keynote by Jon Kleinberg http://t.co/3HUQi1uZj1

    Research to understand discussion and comment threads – #cj2014 keynote by Jon Kleinberg pic.twitter.com/3HUQi1uZj1
  21. Kleinberg now moving from global discussion to local conversations via threads or friends. What makes them engaging, long, short? #cj2014
  22. Tracking the virality of memes: Speed is important. Pics that get the first 1k of shares fast are more likely to go viral after. #cj2014
  23. Content more likely to spread if strangers share it = good reason for journalists to make sure their networks are diverse #CJ2014
  24. #visualization shows 2 kinds of threads: long due to many contributors posting once or convo among few ppl #cj2014 http://t.co/Js2wFv0lyy

    #visualization shows 2 kinds of threads: long due to many contributors posting once or convo among few ppl #cj2014 pic.twitter.com/Js2wFv0lyy
  25. Super interesting question!: why do certain quotes/content stand out? Linguistic markers? #visualization #cj2014 http://t.co/1muOY6tZxI

    Super interesting question!: why do certain quotes/content stand out? Linguistic markers? #visualization #cj2014 pic.twitter.com/1muOY6tZxI
  26. For a week in September 2008, Obama commandeered the news media with the line “lipstick on a pig,” says Jon Kleinberg #cj2014
  27. That would be a nice job description for a business card: Meme tracker. #cj2014
  28. Kleinberg compares memorable & unmemorable movie lines as lab setting to see what features contribute to memorable or viral text #CJ2014
  29. How to track virality of content - use movie quotes: "These aren't the droids you're looking for." #cj2014 http://t.co/Z1YqXGlsgM

    How to track virality of content – use movie quotes: “These aren’t the droids you’re looking for.” #cj2014 pic.twitter.com/Z1YqXGlsgM
  30. Why do we like “these aren’t the droids you’re looking for” but not “you don’t need to see his identification” #CJ2014
  31. Memorable quotes are sequences of unusual words with common part of speech patterns #cj2014 – application to headline writing?
  32. Memorable quotes are less probable in their word choices but more probably in their sentence (part-of-speech) structure – Kleinberg. #cj2014
  33. Jon Kleinberg: Socially shared information - how to predict success stories? Try a sequence of unusual words.#cj2014 http://t.co/AVzW3vImS6

    Jon Kleinberg: Socially shared information – how to predict success stories? Try a sequence of unusual words.#cj2014 pic.twitter.com/AVzW3vImS6
  34. Is there an algorithmic pattern to why a movie quote is memorable? Take “you had me at hello.” What’s so special about it? #cj2014
  35. “Memorable quotes need to have a certain portability” _Jon Kleinberg #cj2014
  36. Memorable quotes tend to be more ‘general’: more present tense, indefinite articles, fewer third-person pronouns >> ‘portability’ #cj2014
  37. #CJ2014 The ‘You had me at hello’ paper reference by Jon Kleinberg (including movie quotes memorability test):  http://www.mpi-sws.org/~cristian/memorability.html 
  38. Slogans in #advertising are like memorable quotes. “It just keeps going & going & going.” | #marketing #NLP #CJ2014
  39. Is there an analogy of genetics for text: ‘fitness’ of text for sharing, mutation of ‘junk’ parts of quotes while core parts remain #cj2014
  40. #cj2014 Just as genes have functional parts and junk parts, so does text - Beautiful analysis of content prolongation http://t.co/oFsLnMmrN7

    #cj2014 Just as genes have functional parts and junk parts, so does text – Beautiful analysis of content prolongation pic.twitter.com/oFsLnMmrN7
  41. “Genetic analogies for memes are becoming increasingly rich” -Jon Kleingberg #cj2014
  42. Sharing on social networks: “Can cascades be predicted?” — paper by Jon Kleinberg et al  http://bit.ly/1nCkspI  #cj2014
  43. Kleinberg wraps up his fascinating talk with new avenues for computational insight into info flows #CJ2014 http://t.co/vTloP7pllJ

    Kleinberg wraps up his fascinating talk with new avenues for computational insight into info flows #CJ2014 pic.twitter.com/vTloP7pllJ
  44. Great question: What are the features of content that make people STOP watching/reading/commenting? #CJ2014
  45. Another great question: Are there computational ways to evaluate WHO gets to be quoted in the first place? #CJ2014

#ONA13 workshop materials: Using WordPress to Structure your Beat

Materials from the structure your beat session that Stephanie Yiu, Connor Jennings and I presented.

Examples

Politifact

http://www.politifact.com/ (using Django for structure)

– statements

– people (politicians and now pudits)

– legislative bills

– commercials

– states

– true/false spectrum of fact checks

Technically Philly

http://technical.ly/philly/

http://technical.ly/philly/directory/ (uses WordPress)

– people

– organizations

– projects

– expertise

Homicide Watch

http://homicidewatch.org/ (uses Django for structure, WordPress for posts)

Kaiser Family Foundation

has 30+ Custom Post Types that allow for faceting when you search their site:

http://kff.org/search/?s=vaccinations

They combined 10 years of content across 10 CMSes into WordPress:

http://vip.wordpress.com/2013/07/02/kaiser-family-foundation-bringing-20-years-of-data-into-wordpress/

The structured data allows them to generate these maps of State and Global Health Indicators.

http://kff.org/statedata/

http://kff.org/global-indicator/malaria-deaths/#map

General types

  • Crime

  • Education

  • Government

  • Transportation

  • Business

  • Entertainment

  • Arts

  • Restaurants

  • Food/recipes

  • Sports

  • Obits

  • Anything!

How can WordPress help?

Custom post types

http://codex.wordpress.org/Post_Types

http://wp.smashingmagazine.com/2012/11/08/complete-guide-custom-post-types/

Custom meta boxes

http://codex.wordpress.org/Function_Reference/add_meta_box

http://wp.smashingmagazine.com/2011/10/04/create-custom-post-meta-boxes-wordpress/

Plugin

http://wordpress.org/plugins/meta-box

Custom fields

http://codex.wordpress.org/Custom_Fields

Custom taxonomies

http://codex.wordpress.org/Taxonomies

http://wp.smashingmagazine.com/2012/01/04/create-custom-taxonomies-wordpress/

Misc

http://wordpress.org/plugins/post-meta/

http://www.advancedcustomfields.com/