I’m following the Computation + Journalism 2014 symposium via the hashtag and livestream. Below are some highlights I collected from the opening keynote.
Edit
#cj2014: Tracing the Flow of On-Line Information through Networks and Text
Keynote by Jon Kleinberg at 2014 Computation + Journalism symposium at Columbia University
-
Event page:
-
2014 C+J SymposiumWe live in a society that is increasingly dependent on data and computation, a dependence that often evolves invisibly, without substantial critical assessment or accountability. Far from virtual, inert quantities, data and computation exert real forces in the physical world, shaping and defining systems of power that will play larger and larger roles in people’s lives.
-
Highlights from the keynote (in chronological order):
-
Jon Kleinberg at #cj2014 pic.twitter.com/mPoyNMZgeJ -
#CJ2014 Vannevar Bush v. Katz+Lazarsfeld in Kleinberg’s keynote pic.twitter.com/Tsw544TSxZ -
Jon Kleinberg opens #CJ2014 with a ref to the classic essay As We May Think. http://j.mp/ZPWaO1 -
kleinberg on sharing information vs storing/accessing it #cj2014 pic.twitter.com/HRlwZ3ChQI -
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 … -
Kleinberg explains tracking essential elements of a story (like phrases) as they move through networks. #cj2014 pic.twitter.com/V1fiFZWUBS -
Basic question: how to predict what content will be shared widely? Or, are cascades unpredictable? #cj2014 pic.twitter.com/Q7dCleEkXH -
#cj2014 Is virality predictable? You as poster rarely experience it w your content, but you as consumer see it often pic.twitter.com/IEgOmZtWIv -
Temporal features most powerful in predicting resharing of photo memes #CJ2014 pic.twitter.com/3ZKFHIzO7Y -
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 -
Research to understand discussion and comment threads – #cj2014 keynote by Jon Kleinberg pic.twitter.com/3HUQi1uZj1 -
#visualization shows 2 kinds of threads: long due to many contributors posting once or convo among few ppl #cj2014 pic.twitter.com/Js2wFv0lyy -
Super interesting question!: why do certain quotes/content stand out? Linguistic markers? #visualization #cj2014 pic.twitter.com/1muOY6tZxI -
Movie quotes as viral text #CJ2014 pic.twitter.com/lSU8PyeKpW -
How to track virality of content – use movie quotes: “These aren’t the droids you’re looking for.” #cj2014 pic.twitter.com/Z1YqXGlsgM -
Jon Kleinberg: Socially shared information – how to predict success stories? Try a sequence of unusual words.#cj2014 pic.twitter.com/AVzW3vImS6 -
#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 … -
Slogans in #advertising are like memorable quotes. “It just keeps going & going & going.” | #marketing #NLP #CJ2014 -
#cj2014 Just as genes have functional parts and junk parts, so does text – Beautiful analysis of content prolongation pic.twitter.com/oFsLnMmrN7 -
Sharing on social networks: “Can cascades be predicted?” — paper by Jon Kleinberg et al http://bit.ly/1nCkspI #cj2014 -
Kleinberg wraps up his fascinating talk with new avenues for computational insight into info flows #CJ2014 pic.twitter.com/vTloP7pllJ
