Harnessing the power of ML and NLP for decision making in education sector from social media data

Cardiometry

article

Harshita Murthy¹  Hemraj Lamkuche¹ 

[1] Symbiosis Centre for Information Technology, Symbiosis International ,(Deemed University)

关键词: Social Media;    Pandemic;    Tweets;    NLP;    COVID-19;    Sentiment Analysis;    Education;   

DOI  :  10.18137/cardiometry.2022.22.415420

学科分类：环境科学（综合）

来源: Russian New University

【 摘 要 】

The active social media users across the globe have passed the 3.8 billion mark. Platforms like Facebook, Reddit, Instagram, Twitter, and more are an ocean full of opinions and views. With over 500 million tweets being generated daily, this enormous volume of data can offer very prominent insights and allow organizations and businesses to make strategic decisions. The COVID-19 pandemic has changed the landscape of learning and education dramatically. With a sudden deviation from the classroom in many parts of the world, some wonder if the adoption of online learning will continue with the outbreak of the post-epidemic epidemic and how such a change could affect the global education market. The crux of the problem is how we need to analyze vast amounts of data efficiently. We chose to employ advanced ML and NLP techniques to analyze the sentiment of the masses on digital learning and important extracting demographic information from them. In this paper, we will make an effort to understand the orientation of the academicians towards the recent online education adoption. We will collect the data from the tweets using the trending tags of COVID-19 and Online classes.

【 授权许可】

CC BY