Tweets Analysis - Keyword: @migga

Overview

Total number of tweets analysed

110

Earliest tweet was on

2023-02-10

Latest tweet was on

2023-02-20

Tweets covering

10 days

Average age of authors' accounts

8 years


Summarization

Volunteers have been providing user-friendly databases with information regarding Covid-19, such as covidlive, covidbaseau, and more. It has been suggested that such databases should be made public, with equitable analysis of this data. Additionally, government transparency, particularly when it comes to presenting data in an easily accessible format, has been called into question. Volunteers have provided useful summary statistics, but this need should be filled by government in the future. The Base Rate Fallacy, whereby the use of information or data ignores the base rate of the whole population, has been highlighted as particularly dangerous.

Topic Modeling

  1. Data Management/Accessibility
  2. Presentation of Data
  3. Vaccine Status Analysis
  4. Infographic Use
  5. Base Rate Fallacy

Emotional Analysis

The emotions expressed in these tweets range from admiration and appreciation for the work of those compiling data on Covid-19 to frustration and anger at the lack of data transparency and utility. There is a sense of urgency in the need for reliable and accessible data, as well as a feeling of disappointment in the way governments have handled the situation. There is also a sense of determination and resilience, as those working on data solutions continue to strive to make information more accessible and understandable.

Trend Analysis

  1. Covid-19 related data, trends and statistics
  2. User-friendly and accessible databases
  3. Incomplete data sets and data inaccuracies
  4. Data misuse and misinterpretation
  5. Transparency and independent data presentation

Disclaimer: The text analysis on twtdata.com, powered by OpenAI, does not represent the views of twtdata.com or its affiliates. The analysis is for informational purposes only and not an endorsement of any viewpoint.

Types of Tweets

Number of Retweets

17

Percentage of total tweets

15%

Number of Original tweets

0

Percentage of total tweets

0%

Number of tweets that contain Mentions

110

Percentage of total tweets

100%

Number of tweets that were Replies

93

Percentage of total tweets

84%

Number of tweets that were Quotes

5

Percentage of total tweets

4%

Number of tweets that contain Hashtags

1

Percentage of total tweets

0%


Top 5 devices used to tweet

Source Count
Twitter Web App 45
Twitter for iPhone 38
Twitter for iPad 18
Twitter for Android 9

What devices were used to tweet


Top 10 accounts with highest followers count

Username Name Bio Followers count
MackayIM ɪᴀɴ ᴍ. ᴍᴀᴄᴋᴀʏ, ᴘʜᴅ 🦠🤧🧬🥼🦟🧀 virologist. husband. dad. reader. writer. fixer. bad typist. learner. in no order. opinions mine alone. Also here-https://t.co/KMyCSWJNku 123,658
melissahoyer Melissa Hoyer Contributing lifestyle, travel, news, pop culture commentator. Lecturer. Editor. MC. Consultant. 📺🎙👩🏼‍💻Mumma to son & dog. https://t.co/FTKGBRIWqe 61,700
drkatraphael Rev Dr Kathleen Raphael DD LPN Don't hurt humans or animals. Let's live together & pool resources. #DisabilitiesHappen #NoViolence 🌿 LonelyNoMore 🌱 #Resist 🌊 #YoureGonnaGetOldToo ❤#Love❤ 27,415
dbRaevn dbRaevn Covid cartographer 15,084
CollignonPeter Peter Collignon Infectious Diseases Physician and Microbiologist. Professor Medical School. Australian National University. Views are my own. 13,688
Mike_Honey_ Mike Honey Data Visualisation and Data Integration specialist - Melbourne, Australia🦣 https://t.co/hTTQENXZ3m🦣 @mike_honey_@aus.social 12,182
BigBadDenis Denis - The COVID info guy - Sharing info on COVID since the start of the pandemic. #PandemicIsNotOver 💻 IT Systems Administrator 💪 GYMaHolic 8,757
ACTINOSProject David Caldicott Urgentiste / Disasterologist / Dissident. Handyman to the Human Body. Anti-Viral Agent. Bad typist. Twitter is to keep notes. All opinions are your own. 8,048
DougalBeatty Dougal Beatty Reporter for @9newsmelb | Instagram: dougalbeatty 6,179
KarenCutter4 Karen Cutter Actuary. Australian. Not affiliated with ABS or govt health departments. All views my own. Blocks anti-vaxxers. mastodon:@KarenCutter@aus.social 6,004

Top 10 accounts with highest friends count

Username Name Bio Followers count
drkatraphael Rev Dr Kathleen Raphael DD LPN Don't hurt humans or animals. Let's live together & pool resources. #DisabilitiesHappen #NoViolence 🌿 LonelyNoMore 🌱 #Resist 🌊 #YoureGonnaGetOldToo ❤#Love❤ 28,892
darylgibson Blue-tongue darylgibson@mastodon.social Dosimetry Physics MSc USyd SydneyRadiological Health Physics BSc UMass LowellI hope daz eventually gets covid, it's mild, he realises it's not a problem 6,366
PivaLasVegas Laur 🍊 I can play 'Orange crush' by REM and 'O Valencia' by The Decemberists...and anything by Pulp (although not everyone's a fan). 🏎 & 🍷🥂&😻&♥️🤍🖤&👨‍👩‍👧‍👦 4,998
verbatorium Verbatorium 😷💉❎4️⃣ Politics, Climate Change, Biodiversity. Anti-SARS-CoV-2 Also @mastodon.au #CovidIsAirborne #VaccinesPLUS #WearAMask #Yes23 He/Him. 4,998
MackayIM ɪᴀɴ ᴍ. ᴍᴀᴄᴋᴀʏ, ᴘʜᴅ 🦠🤧🧬🥼🦟🧀 virologist. husband. dad. reader. writer. fixer. bad typist. learner. in no order. opinions mine alone. Also here-https://t.co/KMyCSWJNku 4,834
Boris4T Aussie Warpath Is it possible to wake them up? I don't know... but I am trying to.Come join me :) Infowars fan from Australia. 4,817
aparachick Aparachick 😷 IF YOU DON’T GET COVID, YOU CANT SPREAD COVID.😷💉🚪🪟🌬 You don’t need to abuse someone to make a point. Civility please. Please retweet me, not quote tweet 4,800
watinthe_ SewerRatSam 💉💉💉💉 Politics, human rights, social justice. Passionately supports young people’s creative voice. #VaccinePlus #CleanAir Views my own. @watinthe_@mastodon.social 3,516
TaylorS11264605 TaylorSummers MASKS WORK 4 ALL Variants! - 3,456
ACTINOSProject David Caldicott Urgentiste / Disasterologist / Dissident. Handyman to the Human Body. Anti-Viral Agent. Bad typist. Twitter is to keep notes. All opinions are your own. 2,587

Most active users

Username Bio Number of tweets
KarenCutter4 Actuary. Australian. Not affiliated with ABS or govt health departments. All views my own. Blocks anti-vaxxers. mastodon:@KarenCutter@aus.social 18
dbRaevn Covid cartographer 10
MixtUpMixy Jungle/DnB DJ #Sapiosexual #AlwaysWasAlwaysWillBe #LoveIsLove 🏳️‍⚧️ 🏳️‍🌈 Only the meek get pinched, the bold survive. i’m at mixtupmixy at aus dot social 8
RichardfromSyd1 An IT nerd adrift on the waves of Twitter 6
MackayIM virologist. husband. dad. reader. writer. fixer. bad typist. learner. in no order. opinions mine alone. Also here-https://t.co/KMyCSWJNku 6
darylgibson Dosimetry Physics MSc USyd SydneyRadiological Health Physics BSc UMass LowellI hope daz eventually gets covid, it's mild, he realises it's not a problem 4
aparachick IF YOU DON’T GET COVID, YOU CANT SPREAD COVID.😷💉🚪🪟🌬 You don’t need to abuse someone to make a point. Civility please. Please retweet me, not quote tweet 4
Adzyreturns I shall finish the game 4
djf0001 /SnNot at Mast a don: Not at ttr at aus dot social 4
kazza264 2020 the year where both your first and last name are poison 3

Tweets per day


Top 10 tweets with highest Retweet count

ID Text Retweet count
1627569945600221190 @KarenCutter4 @djf0001 @JohannaSzabo1 @dbRaevn @MackayIM @DeadInLongRun @Mike_Honey_ @aparachick @migga I have this handy infographic I post to everyone with that question 😄 https://t.co/F9FqIDJz5Q 13
1627578527976685569 @JohannaSzabo1 @KarenCutter4 @djf0001 @dbRaevn @MackayIM @DeadInLongRun @Mike_Honey_ @aparachick @migga How about this one? 😇Similar point, different subject.I get what you’re saying though. Our own govt, in their haste to pretend its over, have dulled our tools of debate. https://t.co/IIxQ3nItoV 7
1627414887193530368 @MackayIM @dbRaevn @MixtUpMixy @DeadInLongRun @Mike_Honey_ @aparachick And all of it should be compiled in a user-friendly database covering all of Australia. Sites like covidlive shouldn’t need to exist. @migga and @dbRaevn should be using their valuable talents elsewhere. 6
1627527903822086145 @dbRaevn @JohannaSzabo1 @MackayIM @djf0001 @MixtUpMixy @DeadInLongRun @Mike_Honey_ @aparachick @migga The NSW data was worse than that. The process used to determine vax status was to match to AIR. And if you could be found in AIR you were designated “unknown”. So the data had zero unvaxxed in hospital and loads of unknowns. The anti-vaxxers overlooked the big number of unknowns. 3
1627416450066714624 @KarenCutter4 @MackayIM @dbRaevn @MixtUpMixy @DeadInLongRun @Mike_Honey_ @migga And @covidbaseau and a few other websites. But thank heavens for all of you. Getting this info in an easily digested form from all of you has informed how I mitigate. So many of my friends have no idea of the extent of Covid, quite unbelieving when I tell them. 3
1627419384913489920 @MackayIM @dbRaevn @MixtUpMixy @DeadInLongRun @Mike_Honey_ @aparachick @migga If you were starting with a blank piece of paper and asked “what will the public want to know?” you would end up with something that looks quite different, and much less of a dogs breakfast 3
1626427330448199681 Yesterday Prof Kelly said there were 18,190 covid deaths across the pandemic, which looked low relative to the total of state reporting of 19,070 (from covidlive thanks @migga). His figures for 2022 and 2023 matched the Fed Health department data. https://t.co/814Nq8tkym 2
1626356255832027138 @frilly_edges I wonder if our data people @Mike_Honey_ , @dbRaevn or @migga have any opinions on the data Ms Russell has provided above? Anecdotally on here we see so many stories of children sent to school with COVID, passing it onto others and back into families again. 2
1627448348943978496 @KarenCutter4 @MackayIM @dbRaevn @MixtUpMixy @DeadInLongRun @Mike_Honey_ @aparachick @migga Unless there is a very *very* good reason, all data should be public (to the max extent privacy allows), allowing equitable independant analysis. Data shines a light. Incompetence (or worse) hides in darkness. 2
1627539261066190848 @KarenCutter4 @JohannaSzabo1 @MackayIM @djf0001 @MixtUpMixy @DeadInLongRun @Mike_Honey_ @aparachick @migga Here's an example of this being used to mislead that takes it even further (I've blocked out the source to avoid sharing it). Because the Unknown group doesn't have a defined pop, they used a per-capita rate based on the whole state pop to make it seem irrelevant. https://t.co/gJV6rWvDh1 2

Top 10 tweets with highest Like count

ID Text Like count
1627414887193530368 @MackayIM @dbRaevn @MixtUpMixy @DeadInLongRun @Mike_Honey_ @aparachick And all of it should be compiled in a user-friendly database covering all of Australia. Sites like covidlive shouldn’t need to exist. @migga and @dbRaevn should be using their valuable talents elsewhere. 51
1627569945600221190 @KarenCutter4 @djf0001 @JohannaSzabo1 @dbRaevn @MackayIM @DeadInLongRun @Mike_Honey_ @aparachick @migga I have this handy infographic I post to everyone with that question 😄 https://t.co/F9FqIDJz5Q 39
1627419384913489920 @MackayIM @dbRaevn @MixtUpMixy @DeadInLongRun @Mike_Honey_ @aparachick @migga If you were starting with a blank piece of paper and asked “what will the public want to know?” you would end up with something that looks quite different, and much less of a dogs breakfast 27
1627527903822086145 @dbRaevn @JohannaSzabo1 @MackayIM @djf0001 @MixtUpMixy @DeadInLongRun @Mike_Honey_ @aparachick @migga The NSW data was worse than that. The process used to determine vax status was to match to AIR. And if you could be found in AIR you were designated “unknown”. So the data had zero unvaxxed in hospital and loads of unknowns. The anti-vaxxers overlooked the big number of unknowns. 23
1627578527976685569 @JohannaSzabo1 @KarenCutter4 @djf0001 @dbRaevn @MackayIM @DeadInLongRun @Mike_Honey_ @aparachick @migga How about this one? 😇Similar point, different subject.I get what you’re saying though. Our own govt, in their haste to pretend its over, have dulled our tools of debate. https://t.co/IIxQ3nItoV 21
1627416450066714624 @KarenCutter4 @MackayIM @dbRaevn @MixtUpMixy @DeadInLongRun @Mike_Honey_ @migga And @covidbaseau and a few other websites. But thank heavens for all of you. Getting this info in an easily digested form from all of you has informed how I mitigate. So many of my friends have no idea of the extent of Covid, quite unbelieving when I tell them. 20
1627448348943978496 @KarenCutter4 @MackayIM @dbRaevn @MixtUpMixy @DeadInLongRun @Mike_Honey_ @aparachick @migga Unless there is a very *very* good reason, all data should be public (to the max extent privacy allows), allowing equitable independant analysis. Data shines a light. Incompetence (or worse) hides in darkness. 17
1627460617954295808 @KarenCutter4 @MackayIM @dbRaevn @MixtUpMixy @DeadInLongRun @Mike_Honey_ @migga For me it’s been wanting info to assess how safe it is to be out and about. It’s not about obsessing how many people are dying. It’s protecting my family’s ongoing health status. - how many infections in my local area has been a big one. Stopping mandatory reporting a big blow. 17
1626356255832027138 @frilly_edges I wonder if our data people @Mike_Honey_ , @dbRaevn or @migga have any opinions on the data Ms Russell has provided above? Anecdotally on here we see so many stories of children sent to school with COVID, passing it onto others and back into families again. 14
1627539261066190848 @KarenCutter4 @JohannaSzabo1 @MackayIM @djf0001 @MixtUpMixy @DeadInLongRun @Mike_Honey_ @aparachick @migga Here's an example of this being used to mislead that takes it even further (I've blocked out the source to avoid sharing it). Because the Unknown group doesn't have a defined pop, they used a per-capita rate based on the whole state pop to make it seem irrelevant. https://t.co/gJV6rWvDh1 14

Top 3 Languages Used In Tweets


Top 10 Hashtags used

Hashtag Count
#transparency 1

Top 10 Hashtags Used In Tweets

Top 10 mentions

Mention Count
@migga 111
@mike_honey_ 82
@aparachick 80
@deadinlongrun 77
@dbraevn 75
@mixtupmixy 69
@mackayim 66
@karencutter4 61
@djf0001 52
@johannaszabo1 43

Top 10 mentions

Wordcloud of Tweets


Emojis

Average number of emojis used per tweet

21

Emojis used in tweets

Emoji Count Emoji Text
😄 2 grinning_face_with_smiling_eyes
😇 2 smiling_face_with_halo
💯 2 hundred_points
👍 2 thumbs_up
🤡 2 clown_face
😉 2 winking_face
😂 2 face_with_tears_of_joy
😘 1 face_blowing_a_kiss
🤔 1 thinking_face
🤷🏻‍♀️ 1 woman_shrugging_light_skin_tone

Emojis groups

Emoji Group Count
Smileys & Emotion 19
People & Body 3
Animals & Nature 1
Travel & Places 1