Context
The data is about users tweets about valorant agents, Valorant is a free-to-play first-person FPS hero shooter developed and published by Riot Games
Agents are continuously updated with buffs or nerfs or adding new agents, the goal here is to do Sentimental Analysis using NLP and Deep Learning techniques.
Content
These are our columns
tweet: contains the main text of the tweet and each tweet associated with certain agent
date: the date when tweet published
Agent: the Agent name of which the tweet contains
Role: the Agent type we have various roles in the game Duelists, Controllers, Initiators, Sentinels
Acknowledgements
I got these data using twitter API you can see the code used to get the data Here
I will continuously update the data every new patch
Inspiration
- you can do sentimental analysis with the tweets to see
- what is the most positive/loved agent ?
- what is the most positive/loved role ?
- the text of tweets isn't clean you have to do some text cleaning with NLP like removing mentions , analyzing emojis, etc ...