savmontano - Tweet Data Analysis

Tweets Analysis - Keyword: @savmontano

Publie le 08/03/2023

Resume

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

Resume

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.

Modelisation des Sujets

  • 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

Analyse des Sentiments

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.

Analyse des Tendances

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

Avertissement : L'analyse de texte de twtdata.com utilise OpenAI et ne represente pas les opinions de twtdata.com ou de ses affilies. L'analyse est uniquement a titre informatif et ne constitue pas une approbation d'une quelconque opinion.

Types de Tweets

Number of Retweets

7

100% du total

Number of Original tweets

0

0% du total

Number of tweets that were Quotes

0

0% du total

Number of tweets that were Replies

0

0% du total

Number of tweets that contain Hashtags

0

0% du total

Number of tweets that contain Mentions

7

100% du total

Appareils Utilises pour Tweeter

Top 5 Appareils

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

Repartition des Appareils

Appareils utilises pour tweeter

Top 10 Comptes par Abonnes

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 Comptes par Abonnements

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

Utilisateurs les Plus Actifs

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 par Jour

Graphique des tweets par jour

Principales Langues Utilisees

Langues utilisees dans les tweets

Top 10 Hashtags

Top 10 Mentions

Mention Count
@savmontano 7
Top mentions

Nuage de Mots des Tweets

Nuage de mots des tweets

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