As per the current global scenario, two very important topics of discussion are COVID and Ukraine war. These two issues have impacted lives across the world. These issues are very critical and have triggered sentiments globally. India and USA are two bigger countries and have faced many challenges due to these two global issues. India and USA are democratic, diverse in nature, and belong to two different continents of the world where the USA is a developed country and India is a developing country.  Based on these considerations, this study was focused on analyzing the relationship between the trending topic and the tweet’s location of origin. The analysis was performed on the Twitter sentiment data related to different locations within India and The USA.  As the data from Twitter is unstructured, it was cleansed and preprocessed before conducting sentiment analysis. The cleansed and processed data were used for sentiment analysis using Valence Aware Dictionary and Sentiment Reasoner VADER tool. Based on the sentiment analysis results the tweets were classified as positive, negative, and neutral.   To compare sentiment across locations, the total sentiment value of the location was normalized by its proportion to the population. During this project best all aspects of data science were utilized, which includes cleansing, processing, modeling, text analytics, analysis, and visualization of the data. This study aimed to find meaningful patterns so that the relationship between location and sentiment can be identified and utilized in future studies and business planning.