General observations
Out of 35,969 geotagged tweets analysed, about 63% were negatively classified, and almost 37% were positively classified. Most of the negatively classified tweets were posted during the pre-concave stage (70%). About 63% of the tweets circulated within the concave-up and linear stages carried negative sentiments. The concave-down stage had the least percentage of negatively classified tweets (62%). Majority of the negatively classified tweets were tweeted from NSW, VIC, WA, and ACT people. Accordingly, in these states and territories, there were 9,885 more negatively classified tweets than the positively classified tweets.
The concave-up stage is the most critical period of a pandemic curve. During this period the number of confirmed cases rapidly increase within a shorter time period. Nonetheless, the Australian government developed 14 major responses to control the dispersion of COVID-19. Accordingly, on average, the concave-up stage of Australia lasted only for around 16 days and 29% of the total tweets were circulated within this shorter time period.
Suppression measures
Transmission of COVID-19 can be categorised into (a) Small chains of transmission, and; (b) Large chains resulting in extensive spread. Countries such as Taiwan and New Zealand took strong measures at the earliest, and ended up in small chains of transmission. The countries that have not taken strong measures at the earliest ended up in large chains of transmission such as USA and Brazil (Anderson et al., 2020).
Australia took strong actions to fight with this new pandemic. On 25th January 2020, the first COVID-19 patient was confirmed, who had flown to Melbourne from Guangdong Province of China on 19 January 2020 (Department of Health, 2020b). On 1 February 2020, Australian government blocked China arrivals to the country. Since then, until 4 May 2020, Australian government has developed 14 major responses—so-called pandemic responses—to control spreading the COVID-19 in Australia, and another 7 major responses—so-called economic responses—to address the economic downturn (Australian Government, 2020b). These 21 major governmental responses are listed in Table 2, and also marked in Fig. 5 to 12.
Table 2 Major responses undertaken by the Australian government to combat COVID-19
No
|
Date
|
Response
|
1
|
01/02/2020
|
Blocked China arrivals*
|
2
|
29/02/2020
|
Blocked Iran arrivals*
|
3
|
05/03/2020
|
Blocked South Korea arrivals*
|
4
|
11/03/2020
|
Blocked Italy arrivals*
|
5
|
13/03/2020
|
Outdoor gatherings limited to 500 persons*
|
6
|
16/032020
|
Self-isolation for overseas travellers, cruise ships blocked for 30 days*
|
7
|
18/03/2020
|
Indoor gatherings limited to 100 persons*
|
8
|
19/03/2020
|
Borders closed to non-citizens and residents*
|
9
|
20/03/2020
|
Started to pay JobSeeker payments**
|
10
|
23/03/2020
|
Pubs/clubs closed, restaurants take-away only*
|
11
|
24/03/2020
|
Ban on Australians travelling overseas*
|
12
|
25/03/2020
|
Temporarily reduced minimum drawdown rated for superannuation**
|
13
|
26/03/2020
|
Expanded testing criteria*
|
14
|
28/03/2020
|
Mandatory isolation in hotels for all travellers*
|
15
|
30/03/2020
|
Outdoor/indoor gatherings two persons only*
|
16
|
31/03/2020
|
Provided payments of $750 to social security, veteran and other income support recipients**
|
17
|
26/04/2020
|
The COVIDSafe App is released*
|
18
|
27/04/2020
|
Expanded eligibility to income support payments **
|
19
|
27/04/2020
|
Paid the time restricted COVID-19 supplement of $500 which paid per fortnight**
|
20
|
01/05/2020
|
Increased transfer payments from reduced deeming rates**
|
21
|
04/05/2020
|
Started to pay JobKeeper payments**
|
Note: *Health response; **Economic response
|
Fig. 4 shows the dispersion of confirmed COVID-19 cases, deaths, the tweets circulated in Australia and the responses undertaken by the Australian government to stop the spreading of COVID-19. As shown in Fig. 4, the number of tweets and the number of confirmed cases have a positive relationship with a statistical correlation of 0.72 at 0.05 significance level. This shows that the number of tweets changed according to the number of confirmed cases. Furthermore, Fig. 4 emphasised that 21 major governmental responses (14 health and 7 economic) to the pandemic undoubtedly have led to the flattening of the COVID-19 pandemic curve of Australia.
When governments respond to a pandemic, their economy also get affected. Hence, taking strong economic responses simultaneously with pandemic responses is important to battle a pandemic effectively (Australian Government, 2020b). Among such responses, community welfare needs to be given priority as people go out of jobs due to unprecedented pandemic responses such as social distancing, self-isolation, and restriction to mass gatherings. As listed Table 2, Australian government introduced 7 major economic responses within the study period. They were oriented towards delivering funds to the financially struggling people, and unemployed. Additionally, the federal government decided to reduce social security deeming rates. Accordingly, on 1 May 2020, the upper and lower deeming rates were 2.25% and 0.25% respectively. These reductions created a low interest environment, which benefitted around 900,000 income support recipients, and around 565,000 pensioners.
Albeit, the community perceptions towards such ‘radical’ and ‘unprecedented’ measures need to be reviewed closely and thoroughly. Most significantly, during pandemic situations, where social distancing is a must, social media analytics can help policy- and decision-makers to screen community behaviours without reaching the community directly. Fig. 5 to 12 illustrate the distribution of positively and negatively classified tweets in all Australian states and territories—along with the number of infection cases and deaths. In Australia, the only state/territory that did not experienced the COVID-19 concave-up stage was NT (Fig. 12). This is due to successful execution of health responses in line with the hammer and dance approach (presented in the literature background section). In the case of VIC, the last week of the analysis (27 April to 04 May 2020) has shown an increase in the confirmed cases. Hence, that week was registered as the second linear stage (Fig. 5). This is an example of pandemics not having a consistent pattern. Without the right responses and interventions, a second wave could be experienced.
In all figures presented, there was a small twitter peak in the pre-concave stage, when there was no significant number of confirmed cases. Such unusual twitter peaks provide an indication of a possible disaster, an unusual behaviour in the environment, or a special community demand (Castilo et al., 2012; Feng & Sester, 2018; Kankanamge et al., 2020a). Thus, mining the perceptions of the general public via social media platforms during a pandemic is essential for policy- and decision-makers to take people-centric decisions, while adhering to the regulations of social distancing and so on.
Positive Community Perceptions
Pre-concave
Only 30% of the total tweets circulated within this stage carried positive perceptions. In NT, the number of positive tweets (n=105) in this stage was high compared to the number of negative tweets (n=65). By contrast, TAS, SA, and QLD had more negative tweets than positive ones, though their difference is comparatively small.
Among the tweets circulated in NT, the words of people (0.73%), health (0.55%), good (0.55%), family, government (0.45%), and learn (0.41%) were popular among the positively classified tweets. People from TAS used the words of people (2.09%), response (1.26%), masks (0.84%), save (0.84%), toilet (0.84%), paper (0.84%), care (0.42%), resources (0.42%) frequently in tweets with positive sentiments. In SA people used testing (1.09%), management (0.9%), health (0.81%), shutdown (0.98%), people (0.65%), toilet (0.58%), and help (0.45%) often to express their positive attitudes. People from QLD frequently used health (0.91%), good (0.88%), quarantine (0.84%), test (0.7%) and reaction (0.46%) words to express their positive ideas. Table 3 shows the example tweets circulated related to the abovementioned words.
Table 3 Example tweets with positive sentiments circulated within pre-concave stage
Date and time
|
State
|
Keyword
|
Exemplar tweet
|
26/02/2020 21:12
|
SA
|
Health
|
Australian health comes before the studies of coronavirus in Australia #auspol
|
30/03/2020 13:27
|
NT
|
Family
|
Coronavirus wedding, Melbourne family allowed to celebrate!
|
16/03/2020 08:07
|
SA
|
Shutdown
|
The Australian arts and events sector MUST be supported during the coronavirus shutdown
|
23/01/2020 22:46
|
QLD
|
Tests
|
Here in Queensland to date we’ve already tested 4 people all 4 came back negative 2 waiting on results
|
07/03/2020 14:27
|
TAS
|
Resources
|
At work we’ve put together some coronavirus info & resources to support people living with disability. Please feel free to share with anyone it may help
|
NSW, VIC, WA and ACT had comparatively less positive tweets. Nevertheless, in general the words such as survive, health, good, young, support, protect, care, and family were frequent among the positively classified tweets circulated within the aforesaid states/territories.
Concave-up
Around 37% of the total tweets circulated within this stage carried positive sentiments. TAS, SA, and QLD had more positive tweets compared to other states and territories. NT did not go through the concave-up stage due to the low number of confirmed COVID-19 cases mainly because NT practiced the hammer and dance successfully, where the identified small COVID-19 patient clusters were strictly hammered by the enacted measures.
People from TAS repeatedly used the words of positive sentiments such as good (0.92%), block (0.74%), immediate (0.65%), health (0.63%), care (0.56%), ban (0.51%), support (0.42%), and prepare (0.41%). The tweets circulated within SA with positive sentiments mostly carried the words of health (0.99%), shutdown (0.98%), people (0.65%), expect (0.57%), distance (0.57%), enjoy (0.53%), isolate (0.45%), and help (0.45%). The words such as people (0.78%), practice (0.75%), health (0.57%), care (0.41%), stay (0.41), and expect (0.4%) were popular among the tweets with positive sentiments circulated in QLD. Table 4 shows the example tweets circulated related to the abovementioned words.
Table 4 Example tweets with positive sentiments circulated within concave-up stage
Date and time
|
State
|
Keyword
|
Exemplar tweet
|
17/03/2020 04:47
|
TAS
|
Shut
|
PM lockdowns the country Australian shut turn weeks actions managed essential services supply chains protected coronavirus impact for months #auspol
|
05/04/2020 07:16
|
SA
|
Distance
|
Day thirteen covid isolation keeping distance. casual Thursday catch covid19 create with every breath custom we make it #supportsmallbusiness #sunstatejewellers #sunstate# jewellers
|
09/02/2020 06:46
|
QLD
|
Enjoy
|
Enjoying Netflix series pandemic moment interesting watch reiterated fact antivaxxers insane #quickdetector
|
14/03/2020 12:09
|
TAS
|
Practice
|
Support promoting positive mental health wellbeing practices pandemic news climate greatly appreciated
|
21/03/2020 21:44
|
SA
|
Health
|
Patients declared, corona virus south Australia declared safe released #hospital #happy #response #senseurgency #australian #healthcare #industry
|
NSW, VIC, WA, and ACT had lesser tweets with positive sentiments during this stage compare to the other states/territories. Nevertheless, the words such as people, health, good, motivate, care and help were plural in the limited number of positively classified tweets in the abovementioned states/territories.
Linear
About 37% of the total tweets circulated in this stage were classified as tweets with positive sentiments. This is the period, when the number of daily reported cases gradually increase at an equal/slower rate than in the concave-up stage. Consequently, more positive tweets can be expected from this stage. Similarly, QLD, SA, TAS, and NT had more tweets with positive sentiments than other regions.
The most frequently used words in QLD were, lives (0.95%), prevent (0.72%), online (0.72%), distance (0.6%), support (0.54%), advice (0.48%), and family (0.48%). Tweets with positive sentiment values circulated in SA included more words such as people (1.1%), lives (0.79%), advantage (0.71%), health (0.65%), government (0.52%), stay (0.46%), quarantine (0.43%), family (0.42%), and care (0.4%). People form TAS had more tweets in this phase related to the words of people (0.78%), health (0.59%), check (0.44%). NT community used the words of crisis (0.95%), days (0.72%), distance (0.6%), government (0.48%), and people (0.48%). Table 5 displays the example tweets related to the abovementioned words.
Table 5 Example tweets with positive sentiments circulated within linear stage
Date and time
|
State
|
Keyword
|
Exemplar tweet
|
29/02/2020 21:19
|
QLD
|
Online
|
Social media teachers deliver classes online, countries covid focus appears delivery content students demonstrating evidence learning keen hear thoughts
|
28/03/2020 09:20
|
SA
|
Family
|
Kind positive happy message family quarantine #stayhome positive kind happy documentary covid19 coronavirus #SA australia #adelaide #adelaide #australia
|
15/03/2020 00:01
|
QLD
|
Prevent
|
Maths extensive social distancing read quarantine preventative purposes waiting sick effective strategy flatten covid19 curve
|
14/04/2020 01:00
|
NT
|
Government
|
Australian government launches coronavirus publicity blitz country runs testing kits
|
27/03/2020 08:20
|
TAS
|
Check
|
Remember folks, libraries closed free ebooks library check library’s website
|
Although NSW, VIC, WA and ACT had more negative tweets in this stage, the words such as help, good, safe, family, global, study, and health were popular among the positively classified tweets.
Concave-down
About 38% of the total tweets circulated within this stage carried positive sentiment values. QLD, NT, TAS, and SA had a few more tweets with positive sentiment values than those with negative sentiment values. People (0.74%), safe (0.71%), test (0.66%), fund (0.64%), support (0.64%), app (0.43%), invest (0.41%), care (0.4%), and isolate (0.4%) were the mostly used words in the positively classified word category in QLD. Positively classified tweets circulated within this period in NT carried words such as approach (4.76%), good (4.76%), herd (4.76%), and immunity (2%). People from TAS used government (0.86%), attitude (0.74%), app (0.72%), family (0.58%), distance (0.43%), vaccine (0.43%), and safe (0.41%). SA people used the words such as good (0.92%), app (0.61%), track (0.6%), normal (0.57%), vaccine (0.54%), claim (0.5%), and days (0.46%) often in the tweets with positive sentiments. Sample tweets circulated related to the frequently used words are given in Table 6.
Table 6 Example tweets with positive sentiments circulated within concave-down stage
Date and time
|
State
|
Keyword
|
Exemplar tweet
|
24/04/2020 06:36
|
TAS
|
App
|
Fully understand downloading covidsafe app doesn’t automatically prevent virus, but it’s a good initiative
|
12/04/2020 14:40
|
SA
|
Normal
|
Covid19 permanently normalise virtual technologies judging zoom meetings
|
23/04/2020 22:41
|
TAS
|
Vaccine
|
AAMRIS members projects progress relating covid19 covering vaccines drug trials diagnostics screening tests mental health indigenous health
|
11/04/2020 15:46
|
QLD
|
Fund
|
Scott Morrison pressed abc730 virgin australia’s request 14b loan bailout pm suggests industry superannuation funds to super fund step fed govt #abcnews #twuaus #coronavirus #virginaustralia
|
29/04/2020 04:48
|
NT
|
Immunity
|
Pretty great idea herd immunity approach controlling spread virus
|
NSW, VIC, WA, and ACT also had comparatively a low number of positively classified tweets related to this stage. Among them, the words such as tests, stay, support, health, learn, people, help, good and school were popular.
Negative community perceptions
Pre-concave
Almost 70% of the total tweets circulated within this stage carried negative sentiments. VIC, NSW, ACT, and WA had more negative tweets than positive ones (Fig. 7). VIC confirmed the first Australian COVID-19 patient on 25 January 2020 (Department of Health, 2020c). Since then, confirmed cases emerged across the state. The words such as arrival (1.16%), immediate (0.72%), cases (0.67%), paper (0.62%), catch (0.5%), toilet (0.5%), commodities (0.5%), dead (0.8%), and spread (0.43%) were plural among the negatively classified tweets in VIC. NSW community used the words related to suffer (0.94%), fail (0.73%), cases (0.67%), and death (0.47%) frequently in the tweets shared. Tweets classified as negative in ACT included words such as die (1.06%), cases (0.81%), arrive (0.69%), and days (0.52%). The words such as hard (1.56%), contract (1.51%), die (0.93%), buy (0.67%), work (0.59%), affect (0.46%), panic (0.4%) were often used in WA.
Table 7 Example tweets with negative sentiments circulated within pre-concave stage
Date and time
|
State
|
Keyword
|
Exemplar tweet
|
02/03/2020 02:12
|
VIC
|
Fail
|
Making sickening joke of Morrisons plan he has on potential carriers of coronavirus looking tends be part of widespread failure of LNP While AFP are looking all wrong places auspol
|
29/01/2020 08:58
|
NSW
|
Suffer
|
Interesting. Last heard some people had virus were reinfected afterwards Apparently did not develop an immunity 2 virus Inoculate supposed trigger the effect yet hears sufferers developed any type immunity reinfect may wrong
|
30/03/2020 00:06
|
VIC
|
Arrival
|
Need to assure that the community evacuees from diamond princess cruise be heavily screened before their arrival
|
28/02/2020 02:45
|
ACT
|
Dead/die
|
Media bull shit Corona Get Common cold die FFS peoples together think percentages not raw numbers wealthy worry does homelessness poverty pure desperation fellow countrymen not move more
|
25/01/2020 05:53
|
WA
|
Hard
|
Moneys come hard during pandemic
|
Although QLD, SA, TAS, and NT had more positive tweets than negative ones in this stage, the words such as spread, risk, infect, flu, work, China, business, death, and panic were common among the negatively classified tweets.
Concave-up
During this phase the number of tweets with negative sentiments (63%) were significantly high compared to the number of positive tweets. For instance, the number of negatively classified tweets in NSW and VIC were almost the twice of the positively classified tweets. Besides, both ACT and WA had more negative tweets than positively classified tweets circulated within this stage.
Most of the negatively classified tweets circulated within NSW carried the words such as cause (1.26%), work (1%), fail (0.76%), travel (0.76%), immediate (0.68%), hard (0.64%), cases (0.57%), control (0.48%), collapse (0.42%), and death (0.4%). Within the tweets from VIC, arrival (1.41%), travel (0.87%), immediate (0.7%), cases (0.49%), and lives (0.41%) were the most popular. People from ACT used more words such as die (1.39%), affect (0.51%), mortgage (0.43%), and suffer (0.42%). The words such as die (1.18%), work (0.77%), hard (0.72%), check (0.65%), suffer (0.5%) and cases (0.42%) were used frequently in the tweets circulated within WA. Table 8 lists the example tweets circulated related to the abovementioned words. These tweets showed economic challenges experienced by the local community such as unemployment and difficulty in paying mortgages.
Table 8 Example tweets with negative sentiments circulated within concave-up stage
Date and time
|
State
|
Keyword
|
Exemplar tweets
|
06/03/2020 14:28
|
WA
|
Die
|
15 MILL people will die best-case coronavirus scenario
|
15/03/2020 04:12
|
VIC
|
Arrival
|
Advice on how self-isolate on arrival Australia please see their Dept of Health’s guide COVID which covers this. Don’t create take risk
|
03/03/2020 08:20
|
NSW
|
Work
|
Can’t stop COVID19 without protecting our health workers he said prices surgical masks increased sixfold while cost ventilators had tripled he added
|
17/03/2020 21:06
|
ACT
|
Mortgage
|
Wouldn’t nice Aussie government absorb rent mortgages during hard times COVID-au
|
4/03/2020 07:46
|
NSW
|
Cause
|
Who think coronavirus would cause toilet paper apocalypse
|
The negatively classified tweets circulated within QLD, SA, and TAS included the words such as employment, spread, panic, confirm, business, risk, fear, anxious and cuts frequently.
Linear
Similar to the concave-up stage, 63% of total tweets circulated within this stage were negative. NSW, VIC, WA, and ACT had more tweets with negative sentiments.
The words such as lives (0.97%), national (0.53%), contract (0.48%), offices (0.44%), stop (0.43%), positive (0.44%), prevent (0.42%) and employer (0.4%) were popular among the tweets circulated in NSW in this phase. Tweets circulated within VIC carried more words such as arrival (1.18%), immediate (0.89%), employment (0.73%), die (0.6%), check (0.56%), positive (0.5%), cases (0.45%), and days (0.44%). The words such as suffer (1.2%), arrival (1%), hard (0.71%), work (0.66%), and dead (0.47%) were frequently used in the tweets circulated within WA. Tweets collected from ACT had more words such as work (0.96%), causes (0.84%), cases (0.57%), government (0.42%), and spread (0.41%). Example tweets related to the abovementioned words are given in Table 9.
Table 9 Example tweets with negative sentiments circulated within linear stage
Date and time
|
State
|
Keyword
|
Exemplar tweet
|
27/03/2020 02:33
|
NSW
|
Arrival
|
Face masked ship crew arrive Sydney amid coronavirus warnings
|
19/03/2020 09:53
|
VIC
|
Employment
|
Really You don’t think shutting down schools and keeping kids home won’t make them stressed How about when there’s mass unemployment and Great Depression kids be stressed then There’s longer game here then just virus
|
20/03/2020 07:25
|
WA
|
Suffer
|
Watching Simpsons ep Bart tricks everyone cruise ship the world suffering virus they stay quarantined How often they predict future
|
18/03/2020 08:25
|
ACT
|
Work
|
People own business works themselves markets shows losing job no help coronavirus
|
11/03/2020 07:03
|
NSW
|
Lives
|
Scott Morrison MP Greg Hunt MP please before become China/Italy stop mass gatherings lock down few weeks could make huge difference how many Aussies become ill coronavirusaustralia you will be saving lives pandemic
|
Although QLD, SA, TAS and NT did not have more negatively classified tweets related to this stage, the words such as employment, death, issue, work, cuts, and businesses were popular among the negatively classified tweets.
Concave-down
Australia did not experience high infection cases and resulting deaths compared to other countries such as USA, Brazil, UK, and Italy. Within a shorter time period Australia was able to control the pandemic situation. Soon after, the gap between negatively and positively classified tweets was narrowed down. However, still, 62% of the total tweets circulated within this phase were negative. NSW, VIC, ACT and WA had more negative tweets than positive ones. The tweets generated from the aforementioned states and territories in this stage either showed the reflections of the community about the life they experienced during the past days or the issues and problems they have to face in the upcoming new normal era.
Most of the tweets from NSW were generated around the words of employment (0.84%), dead (0.55%), cases (0.53%), contract (0.53%), days (0.51%), novel (0.48%), direction (0.46%), experience (0.46%), and cautious (0.4%). Tweets from VIC had more words related to suffer (1.28%), die (0.66%), positive (0.53%), cases (0.53%), care (0.5%) and days (0.47%). Tweets from ACT mostly carried the words such as days (0.62%), check (0.54%), die (0.5%), and cases (0.4%). The words such as employment (0.7%), days (0.59%), check (0.57%), people (0.55%), backward (0.53%), cases (0.48%), hard (0.47%), and miss (0.45%) were the most popular in WA. Sample tweets circulated related to the frequently used words are given in Table 10.
Table 10 Example of tweets with negative sentiments circulated within concave-down stage
Date and time
|
State
|
Keyword
|
Exemplar tweets
|
22/03/2020 23:54
|
WA
|
Employment
|
Surely you can better your employees Armguard COVID19 NO masks NO gloves NO antibacterial wipes ATMs would hive spreading germs well notes misinformation too responsibility the project
|
24/04/2020 06:45
|
VIC
|
Suffer
|
Proud Daniel Andrews MP not giving populist attitude demands sticking restrictions coronavirus crisis Another week doesn’t hurt anyone even though suffer financially etc
|
27/03/2020 04:33
|
ACT
|
Days
|
Australia records highest single day increase coronavirus cases
|
03/04/2020 20:35
|
NSW
|
Employment
|
Impact vast International student’s university school employment Coronavirus COVID-AU
|
18/04/2020 02:23
|
NSW
|
Dead
|
Nearly lost Two people laughed me told couldn’t use fitting rooms virus exactly funny deadly virus killing people over world
|
Compared to other states and territories, the numbers of negatively classified tweets were slightly low in QLD, SA, TAS. Nevertheless, the words such as employment, business, people, cases, spread, suffer, and industry were popular among the negatively classified tweets in QLD, SA, TAS and NT.