Given that we all need air to survive and air is all around us, the haze was a unique event that affected all people in Singapore. At the time, it seemed as if the haze was all we could think about. Local media covered almost nothing but haze for several days. Office chatter and neighborly greetings were abuzz with talk of the haze. Some people took to checking the PSI (Polution Standard Index) readings obsessively.
Our personal observations suggested that haze was on everyone’s mind. But is there a way to measure the consciousness of Singaporeans during the haze to know their thoughts and feelings? Is there a way to quantify the impact of the haze on human activity?
In this data research work, LARC combines the knowledge and expertise of researchers from SMU School of Information Systems and School of Social Science to study social media usage by Singapore users during the haze event so as to derive some insights about people’s reactions to the haze. We analyze several aspects including tweet activities, topics, emotional states, sources of information, and physical behaviors.
The figure shows the number of users generating HazeTwitterData.
The top frequent words that appear in HazeTwitterData were manually determined and categorized into four topical categories, namely:
We examined the emotion state of users by classifying the tweets into the categories below according to the emotion associated keywords.
To determine the information sources referenced by Twitter users during the haze event, we examined the highly mentioned and retweeted URL domains among haze related tweets. The URL domains were categorized into three categories below:
|Domains from news media are highlighted in blue|
|Domains from government are highlighted in green|
|Other Domains are not highlighted|
Domains mentioned in September and October 2015
147,465 haze-related tweets contain url
Domains retweeted in September and October 2015
108,083 haze-related retweets contain url
4SQData were analyzed to study the impact of haze to user activities and businesses. The chart shows foursquare check-in’s trend in September 2015 by location category. We observe four categories of check-in’s: