Analyzed and discussed on the research question, " To what extent can public sentiments on social media platforms such as twitter influence national or global policies on climate change?".
Performed data discovery, cleaned twitter data, classified them as 'anti', 'news', 'pro' and 'neutral' to understand how the tweet's sentiments are analyzed to formulate policies.
The project design involves Exploratory Data Analysis, Extraction of buzz words across different categories, Named Entity Extraction and evaluating different ML models based on accuracy.