Month: January 2017

Just announced: Data News Tops 2016 Philip Meyer Award for Precision Journalism

IRE (Investigative Reporters & Editors) just announced the 2016 Phili Meyer Award winners:  Data news projects top the list. First-placed “Doctors & Sex Abuse” by Atlanta Journal-Constitution, second-placed “How Fire Feeds” by Reveal from The Center for Investigative Reporting, and third-placed “The Tennis Racket” by BuzzFeed are all data-driven investigations. Bravos to data news again.

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Data News of the Week | 媒體如何用數據可視化報道2017年香港特首競選

1月16日,國務院宣佈批准政務司司長林鄭月娥及財政司司長曾俊華辭職。截止下午4時,2017年的香港特首選舉已經有至少4位參選人。分別是退休法官胡國興,新民黨立法會議員葉劉淑儀,政務司司長林鄭月娥及財政司司長曾俊華。

下面我們來看看端傳媒南華早報以及香港01對於此次特首選舉的可視化報道:

1.四大熱門特首參選人,誰能得到中央歡心?

(原文請點:四大熱門特首參選人,誰能得到中央歡心?

端傳媒用漫畫形式簡單列舉了參選人的履歷:

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圖:端傳媒設計部

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Data News of the Week | Smog–Nobody can escape from the air pollution

Toxic haze that settled over much of China during the last three weeks has triggered a flight reflex among residents. Today several districts in Hong Kong experienced poor quality air on Sunday that posed a “very high” health risk.

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(Data from Hong Kong Government Air Quality Health Index, Link: http://www.aqhi.gov.hk/en.html)

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Coming soon: New DJ course – Data Visualization for News

HKBU’s Journalism Department is delighted to offer a new course in the coming semester, JOUR2106 Data Visualization for News. The course will be taught by Mr. HU Pili, CTO of Initium Media (Group), which is a leader of data journalism in Hong Kong.

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Data News of the Week | How data tells you about AI

Artificial Intelligence (AI) becoming the buzzword of 2016.

On December 29, 2016, there is a “Master” of the mysterious player started showing up on Tygem and FoxGo servers and went on to play dozens of matches against some of the top Go players in the world.1.jpg

(JUNG YEON-JE/AFP/Getty Images)

Finally, 60 wins and 0 loss of the proud record, Master win this game.

Subsequently, Google’s DeepMind issued a notice, officially confirmed Master (formerly known as Magister) is AlphaGo.

More information: DeepMind’s work in 2016: a round-up

Artificial intelligence is everywhere. But before scientists trust it, they first need to understand how machines learn.

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