How the Twittersphere reacted to the news of Mr Lee Kuan Yew's death

How the Twittersphere reacted to the news of Mr Lee Kuan Yew's death

Organisation: Singapore Press Holdings Ltd (Singapore)

Publication Date: 04/10/2015

Applicant(s)

Description

The death of Singapore's founding father, Mr Lee Kuan Yew, on March 23 led to an overwhelming outpouring of grief in Singapore. Over 450,000 paid their last respects to Mr Lee during his lying in state at Parliament House from March 25 to 28, and over 100,000 lined the streets to say their final goodbyes during the 15.4km funeral procession on March 29. According to Twitter, over 1.2 million tweets related to Mr Lee were sent from March 23 to 30 during the seven days of mourning. We collected and analysed over half a million tweets from March 18 to 30 that contained the terms "Lee Kuan Yew" or #LeeKuanYew. Of the 531,964 tweets collected, 2,697 contain location data. We map out the tweets over this period in our interactive map. We started working on the Twitter project because we wanted to approach the Lee Kuan Yew story from an alternative angle. Given the intense interest on social media over the past two weeks, we felt it would be worthwhile looking at the data to show some trends or patterns in social media on the topic. The platform of choice was Twitter because of it’s usually the first channel of breaking news dissemination, which allows us to measure how fast and wide the news has spread and generated interest. It is also a great platform to work with because Twitter makes its data freely accessible, though with some limits. We used R, a programming language widely used by statisticians and data scientists, to collect the data. It’s the first time we are utilising this programming language for our interactive graphics work. We started collecting data from March 18 because of the fake announcement of Mr Lee's death on that day. The hoax was so widely circulated on social media that CNN and China's CCTV, Sina and Phoenix Chinese News reported it as fact. This gave us sufficient latitude to establish a baseline in terms of the number of tweets per hour on Mr Lee, prior to his death. When the news of his death broke, we could then show the contrast in terms of the tweet distribution on the map and number of tweets per hour on the chart. In the interactive, we show the tweets per hour and the tweet distribution map along the same timeline so readers can see the two interlinked data streams at a glance. We also show the total distribution of tweets in Singapore and on the world map to show the impact of the news at a glance.

Technologies used for this project:

R, D3.js, Leaflet, CartoDB
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