savmontano - Tweet Data Analysis

Tweets Analysis - Keyword: @savmontano

Veröffentlicht am 8. März 2023

Übersicht

Tweets covering

8 days

Latest tweet was on

2023-02-20

Earliest tweet was on

2023-02-11

Total number of tweets analysed

7

Average age of authors' accounts

3 years

Zusammenfassung

The 2009 H1N1 influenza virus created a pandemic across the world with over 200,000 people estimated to have died from it. The virus was able to spread rapidly due to its high rates of transmission from person to person. Risk factors of the virus included obesity, advanced age, and pre-existing medical conditions such as asthma and diabetes. Vaccinations and antiviral medications such as Tamiflu were used to counteract the virus.

Themenmodellierung

  • Politics: discussions of political figures, policies, and events
  • Social Media: discussion of platforms such as Twitter, Facebook, and Instagram
  • Business: discussion of businesses, products, trends, and strategies
  • Education: discussion of schools, universities, and learning systems
  • Culture: discussion of cultural values, attitudes, and customs

Emotionsanalyse

The tweets analyzed express a range of emotions, including happiness, sadness, fear, anger, and confusion. The majority of the tweets express feelings of happiness, with many people expressing excitement about upcoming events and plans. Some tweets express sadness, such as those expressing feelings of loss and disappointment. Fear is also expressed in some tweets, as people express concerns about their safety or the safety of others. Anger is also expressed in some tweets, as people express frustration about current events and situations. Finally, confusion is also expressed in some tweets, as people express confusion about current events and situations.

Trendanalyse

  • School shootings
  • Gun control
  • Gun safety
  • Gun violence
  • Firearm possession

Haftungsausschluss: Die Textanalyse auf twtdata.com, unterstützt durch OpenAI, stellt nicht die Ansichten von twtdata.com oder seinen verbundenen Unternehmen dar. Die Analyse dient nur zu Informationszwecken und ist keine Bestätigung einer Meinung.

Tweet-Arten

Number of Retweets

7

100% vom Gesamten

Number of Original tweets

0

0% vom Gesamten

Number of tweets that were Quotes

0

0% vom Gesamten

Number of tweets that were Replies

0

0% vom Gesamten

Number of tweets that contain Hashtags

0

0% vom Gesamten

Number of tweets that contain Mentions

7

100% vom Gesamten

Verwendete Geräte zum Tweeten

Top 5 Geräte

Source Count
Twitter Web App 4
Twitter for iPhone 2
Twitter for Android 1

Geräteverteilung

Verwendete Geräte zum Tweeten

Top 10 Konten nach Followern

Username Name Bio Followers count
janelliexbabyx3 Janelle Elizabeth sicker than ur average • insta: @jmaddzx3 2.600
patrici38253735 Patricia - 528
marya_medina_ Marya - 162
peterman61anita Anita - 155
savannahv999 $av 9 9 9 a love letter to you 💌 134
kathy_ellzey17 Kathy - 80
GodwinP45216248 Godwin Peter - 28

Top 10 Konten nach Following

Username Name Bio Followers count
patrici38253735 Patricia - 3.209
peterman61anita Anita - 3.039
kathy_ellzey17 Kathy - 1.984
marya_medina_ Marya - 1.659
janelliexbabyx3 Janelle Elizabeth sicker than ur average • insta: @jmaddzx3 1.370
savannahv999 $av 9 9 9 a love letter to you 💌 411
GodwinP45216248 Godwin Peter - 404

Aktivste Nutzer

Username Bio Number of tweets
GodwinP45216248 - 1
janelliexbabyx3 sicker than ur average • insta: @jmaddzx3 1
kathy_ellzey17 - 1
marya_medina_ - 1
patrici38253735 - 1
peterman61anita - 1
savannahv999 a love letter to you 💌 1

Tweets pro Tag

Tweets pro Tag Diagramm

Top verwendete Sprachen

In Tweets verwendete Sprachen

Top 10 Hashtags

Top 10 Erwaenungen

Mention Count
@savmontano 7
Top Erwaenungen

Wortwolke der Tweets

Wortwolke der Tweets

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