Service Discovery in Mobile Ad-Hoc Environments: A Solution Space Analysis
Rajesh Bose · International Journal of Emerging Trends in Engineering Research · 2020
Twitter is now one of the greatest podiums all over the world through which anyone can present his opinion regarding a particular issue.It is a social networking site.Every day, it generates almost 500 million of tweets and the total volume of tweets contains 8TB of data.This data is very much significant if examined, because we are able to draw out salient facts through opinion mining.We can keep an eye at the augmentation of a product or any important affairs or events or a novel fashion in twitter data.The prime objective of this sentiment analysis or opinion mining is to explore emotion, opinion, subjectivity and perspective from a customary text on application of a medicine for the treatment of COVID-19(Corona Virus Disease 2019).We can classify the tweets into positive and negative sentiments in twitter sentiment analysis.The expression 'Cluster' refers to an accomplished method where homogeneous substances are kept in a distinct class and thus a pack of cluster is created.We went on with an analysis and concluded that the application of clustering can hurriedly and precisely differentiate tweets on account of their sentiment scores and thus it gets weekly and firmly positive or negative tweets, if they are clustered, with outcomes of distinct dictionaries.The objective of this paper is to scrutinize discrete viewpoints of clustering sentiment analysis and thus devises a method to make connection with the tweets of the statesmen of some first world, second world and third world countries.The frame of reference in this case is the polarity and subjectivity on the application of drugs for the treatment of COVID-19.