Abstract:
This research titled “Sentiment Analysis on Bangla Conversation Data Using Machine
Learning Approach” is from conversations people's sentiment during the conversation
period can be extracted as valuable information. In the field of NLP, text analysis and
conclusion of any information as summarization can be done by Sentiment Analysis. The
necessity of sentiment analysis of a conversation is increasing because of the use of
conversation for customer support portal in many e-commerce platforms and crime
investigations on digital evidence. Other languages, like English have enriched libraries
and resources for natural language processing but there are very few works done over
Bangla language. Because of the grammatical complexity in Bangla language, it is more
difficult to extract sentiments from Bangla conversation data. That's why it opens the door
of huge scopes of research. A machine learning approach was applied to extract sentiment
from Bangla conversation. For that, Support Vector Machine, Multinomial Naïve Bayes,
K-Nearest Neighbors, Logistic Regression, Decision Tree & Random Forest was used.
From the dataset, extracted information was labeled as Positive and Negative.