{"created":"2020-12-11T15:55:25.349131+00:00","id":6747,"links":{},"metadata":{"_buckets":{"deposit":"ceb28018-b07b-4a9a-ac8a-2186267cc527"},"_deposit":{"created_by":45,"id":"6747","owner":"45","owners":[45],"owners_ext":{"displayname":"","email":"dimennyaung@uit.edu.mm","username":""},"pid":{"revision_id":0,"type":"depid","value":"6747"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/00006747","sets":["1582963342780:1596102355557"]},"communities":["uit"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Analyzing Sentiment of Myanmar Movie Comments Using Naïve Bayes Classifier","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Sentiment analysis is extremely useful in social media monitoring as it allows us to gain an overview of the wider public opinion behind certain topics. It is also the use of Natural Language Processing (NLP) to analyze social comments and determine a deeper context. Due to little research has been done in the domain of Facebook sentiment classification about Myanmar movie comments, this system aims to determine the overall reaction of the movie using Naïve Bayesian machine learning technique. The objective of this system is to extract movie features from the comments, classify the comments into positive and negative and predict the overall polarity of the comments. In the data preparation phase, the system collects movie comments written by Myanmar language in Facebook as a dataset and these comments are first cleaned to reduce noise. Text pre-processing is also done on Myanmar Word Segmentation Version 1.0 of UCSY and movie features are extracted. Classification is made by using Naïve Bayes approach that gives rise to a probabilistic classifier. For evaluation, 10-fold cross validation which is a standard machine learning assessment technique has been performed on a balanced data set of the movie comments. And the performance of the proposed approach was also evaluated using F-measure."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"Sentiment Analysis"},{"interim":"Naïve Bayes"},{"interim":"Facebook"},{"interim":"Myanmar Movie Comments"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2020-12-11"}],"displaytype":"preview","filename":"16. Analyzing Sentiment of Myanmar Movie Comments Using Naïve Bayes Classifier.pdf","filesize":[{"value":"775 Kb"}],"format":"application/pdf","url":{"url":"https://meral.edu.mm/api/files/ceb28018-b07b-4a9a-ac8a-2186267cc527/16.%20Analyzing%20Sentiment%20of%20Myanmar%20Movie%20Comments%20Using%20Nai%CC%88ve%20Bayes%20Classifier.pdf"},"version_id":"9c554203-25f2-44ca-9a30-60ee29b1385a"}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"MURC 2019","subitem_c_date":"24th - 25th May 2019","subitem_conference_title":"Myanmar Universities’ Research Conference","subitem_place":"Yangon"}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Win Win Thant"},{"subitem_authors_fullname":"Ei Ei Mon"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Conference paper"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2019-05-25"},"item_title":"Analyzing Sentiment of Myanmar Movie Comments Using Naïve Bayes Classifier","item_type_id":"21","owner":"45","path":["1596102355557"],"publish_date":"2020-12-11","publish_status":"0","recid":"6747","relation_version_is_last":true,"title":["Analyzing Sentiment of Myanmar Movie Comments Using Naïve Bayes Classifier"],"weko_creator_id":"45","weko_shared_id":-1},"updated":"2021-12-13T00:29:40.067423+00:00"}