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Preprint / Version 1

Understanding Influential Accounts on Twitter

##article.authors##

  • Aarush Shintre Millenium National School

DOI:

https://doi.org/10.58445/rars.53

Keywords:

Twitter, Covid-19, Vaccinations, LDA, Social media analytics, Social Network Research, Sentiment-Analysis, Influence, Python, Pro-vaxx, Anti-vaxx, graph-based, NLP

Abstract

Twitter is a popular microblogging application that has become increasingly popular for its ability to provide a communication platform for people worldwide, on various topics. Data from twitter is incredibly useful in understanding everyday people’s opinions and sentiments in various contexts, including global issues, like the Covid-19 Pandemic, and the subsequent vaccination efforts. Looking at certain trends in sentiments, topics discussed and what popular influential accounts on twitter talk about are all great ways to understand what is relevant and important to people worldwide. 

We tried to understand accounts’ influence, by analyzing tweets spawned on twitter. First, we tried to understand when were covid-vaccine related tweets most popular in the time span of the data, and what factors might have affected popularity of these tweets. We categorized tweets into pro, anti, and neutral sentiments towards vaccinations, and further analysis was conducted on these categories. 

Interestingly, we observed that about 42% of all favorites and retweets received throughout the time span were attributed to pro-vaccine tweets, which made up 30% of all tweets spawned. To understand what topics were discussed through these popular pro-vaccine tweets that helped them gain popularity, we conducted LDA Analysis on them. The pro-vaccine accounts provided information about covid vaccines, including discussions about vaccine efficacy and vaccine administration, which might have helped their tweets gain traction  in the covid-19 vaccine discussion.

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2022-11-02

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