Emphasizing the Environmental Issue by Machine Learning-Based Sentiment Analysis

Abstract

In many academic disciplines, social media has shown its use as a technique for extracting and analysing public opinion. Exploration of unstructured information in thriving social mass media platforms that provide immediate public feedback and also record long-term information might reveal valuable information. Environmental scientists have seen the potential of public opinion and have undertaken much research on this issue. This paper centres its investigation on the extraction of environmental-related information from social media language, specifically focusing on sentiment analysis. This topic aligns with the field of Data Science & Sustainability. The contemporary information science community is mostly concerned with subjects that intersect with environmental concerns and their wider ramifications on sustainability.