Twitter Sentiment Analysis Using Random Forest Algorithm for Live Twitter Data


Twitter Sentiment Analysis Using Random Forest Algorithm for Live Twitter Data

Lohith D S, Nitin Raj

Lohith D S, Nitin Raj "Twitter Sentiment Analysis Using Random Forest Algorithm for Live Twitter Data" Published in International Journal of Trend in Research and Development (IJTRD), ISSN: 2394-9333, Volume-8 | Issue-5 , October 2021, URL: http://www.ijtrd.com/papers/IJTRD22819.pdf

With the evolution of the internet, the magnitude ofdata present within the web has also amplified. There is also alarge volume of information present within the web for itssurfers. And not to forget, there is tons of information generatedevery second. A Social network is a platform for exchangingideas and opinions. Twitter, Facebook, Instagram and Google aresome of the social network giants of the present times. They arerapidly gaining popularity as they allow people to share andexpress their views about topics, have discussions with differentcommunities, or post messages across the planet. The datagenerated by these sites gives ample opportunities for research onsentiment analysis. The Project focuses mainly on sentimentanalysis of Twitter data. The tweets consist of sentences that arehighly unstructured, heterogeneous, and are either positive ornegative or neutral. During this project, we offer a comparativeanalysis of existing techniques for opinion mining like machinelearning and lexicon-based approaches. With the help of variousmachine learning algorithms like Naive Bayes, Random ForestClassifier we provide research on live Twitter data. Based on theexperiments conducted on ML algorithms, we show thatperformance of Random Forest ML model provides betteraccuracy of 80% compared to other ML algorithms

Twitter Sentiment Analysis, Random Forest Algorithm


Volume-8 | Issue-5 , October 2021

2394-9333

IJTRD22819
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