• MEETALI
• AMANDEEP KAUR SOHAL
• MANDEEP KAUR

Sentiment analysis is the process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer's attitude towards a particular topic, product, is positive, negative, or neutral. Sentiment analysis is done to get public opinions and also used for marketing of products to make business strategies on basis of these opinions. It can be used to identify the follower's attitude towards a brand and its products through the use of variables such as context, product reviews, tones, emotions. Different kinds of sentiments that people have towards amazon products or their services are analysed using Amazon data. The best source available to collect the sentiments is internet. Twitter is social networking platform that provides information regarding sentiment of the user’s w.r.t to their purchase of products. In this research, the KNN-LSTM mechanism is applied instead of WDE-LSTM to predict the more accurate sentiments. Python simulator is used to implement the proposed techniques. Around 94.5% of accuracy is achieved approximately. The proposed algorithm also compared in terms of execution times and it shows that the proposed algorithm outperforms in terms of execution time.

Sentiment analysis, SVM, KNN

"MACHINE LEARNING APPROACH FOR SENTIMENT ANALYSIS OF TWITTER DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.284-290, June 2019, Available :http://www.jetir.org/papers/JETIR1906L43.pdf

"MACHINE LEARNING APPROACH FOR SENTIMENT ANALYSIS OF TWITTER DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp284-290, June 2019, Available at : http://www.jetir.org/papers/JETIR1906L43.pdf