In the current digital age, huge amounts of textual data are generated every second through social media, customer reviews, and online discussions. It has become increasingly important to understand the sentiment behind the text. Sentiment Analysis, which is a subfield of natural language processing (NLP), provides a powerful tool to automatically extract and quantify sentiments expressed in text data.
Sentiment Analysis, also known as Opinion Mining, is the process of using Artificial Intelligence to identify and categorize opinions in text data. The main goal is to determine the sentiment conveyed by the author, which can be categorized as positive, negative, or neutral.
TownSense™ provides multiple methods to intake, analyze, and present data. We perform additional data analysis by using Machine Learning to identify patterns of behavior and insight from individual and group engagement. Our User Experience and User Interface makes the process seamless for participants and groups.
Policy Development
Sentiment Analysis is employed in Political Campaigns and Governance to understand public sentiment towards political candidates, policies, and issues.
Sentiment Analysis helps Businesses Analyze customer reviews, feedback, and surveys to gain insights into customer satisfaction and identify areas for improvement.
Sentiment Analysis is utilized in Financial Markets to analyze news articles, social media discussions, and other textual data for sentiment-driven trading strategies.
