SOCIAL MEDIA SENTIMENT ANALYSIS FOR NEWS EVENTS : A BIG DATAAPPROACH (CAHIERS MAGELLANES-NS, 2024)
Researchers from academia and business are becoming interested in social media big data mining due to the exponential growth of social media data on the internet. Sentiment analysis of news events is an important area within this discipline that has received a lot of interest and could enable a number of real-world applications, such as government public opinion monitoring and website recommendation systems. However, when applied to previous volumes of social media big data, existing sentiment analysis approaches present scalability issues because they generally rely on traditional emotion lexicons or supervised algorithms. As a result, we suggest a novel method for sentiment analysis of news stories. In particular, using words and emoticons related to a news event from social media, we create