Brilliant work - thank you Kalev -----Original Message----- From: Air-L [mailto:air-l-bounces@listserv.aoir.org] On Behalf Of Gohar F. Khan Sent: Tuesday, 28 February 2017 6:30 AM To: air-l@listserv.aoir.org; kalev leetaru <kalev.leetaru5@gmail.com> Subject: Re: [Air-L] four visualizations (and open data) from data mining online news at massive scale Interesting stuff Kalev, thanks for sharing it. Cheers, GFK On Tue, 28 Feb 2017 at 6:48 AM kalev leetaru <kalev.leetaru5@gmail.com> wrote:

Apologies for cross-posting - I thought many of you would find of interest

four of my latest pieces on what we can learn about the global structure of

the news media landscape through massive mining of online news, and given

that the underlying datasets are all open, that these might offer great

starting points for many other research questions.

In particular, two of the analyses rely on applying deep learning image

cataloging to more than a quarter billion global news photographs from last

year, one examining visual geocoding and the other looking at semantic

visual clustering using the assigned labels.

One explores what it looks like to combine multilingual textual geocoding

and sentiment analysis (both covering 65 languages) to process a quarter

billion news articles and 2.2 billion location mentions to map "global

happiness" as seen through the eyes of the world's online news media.

The final leverages visual document extraction to compile three quarters of

a billion outlinks from 121 million articles over the last 10 months and

uses that link graph to explore how global media outlets link to each

other. What makes this particular analysis distinct is both the global

scope (crossing all countries and 65 languages) and the use of the article

link graph rather than the page link graph as is traditionally done (ie

looking at only the links in the article text itself, rather than the

myriad links found in the rest of the surrounding page, such as

headers/footers/advertisements/etc).

Thought these might be of interest re what it looks like to apply these

techniques at scale and with a globalized scope and the open availability

of the underlying computed datasets to enable all kinds of other research

on online news.

http://www.forbes.com/sites/kalevleetaru/2017/02/27/creating-a-massive -network-visualization-of-the-global-news-landscape-who-links-to-whom/

http://www.forbes.com/sites/kalevleetaru/2017/02/25/what-does-artifici al-intelligence-see-in-a-quarter-billion-global-news-photographs/

http://www.forbes.com/sites/kalevleetaru/2017/02/21/visual-geocoding-a -quarter-billion-global-news-photographs-using-googles-deep-learning-a pi/

http://www.forbes.com/sites/kalevleetaru/2017/02/22/mapping-global-hap piness-in-2016-through-a-quarter-billion-news-articles/

~K

http://kalevleetaru.com/

http://blog.gdeltproject.org/

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