{"_buckets": {"deposit": "378a331e-33fc-48de-b9b7-720951a9dc39"}, "_deposit": {"created_by": 73, "id": "7702", "owner": "73", "owners": [73], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "depid", "value": "7702"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/00007702", "sets": ["user-miit"]}, "communities": ["miit"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Sentiment Analysis of the Smart Phone Product Reviews", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Nowadays, social media has become a platform of online communication for people to convey their opinions to the public. Today users can not only obtain information but also actively generate content using web. Blogs, reports, forums, etc. are the main sources of public opinion information called reviews. Good responses from people can awake desire for a product, create brand awareness, encourage a positive attitude toward the product for buying the products. Using natural language processing the text that contains both cases and opinion could be extracted to get some opinionated views. To analysis such texts and reviews sentiment analysis is used. Sentiment analysis is a sub domain of Natural Language Processing and is used to automatically mine the opinions and emotions from text such as comments and posts. In this paper sentiment analysis is carried out by two approaches: machine learning approach and dictionary based approach. And then discuss accuracies for more accurate sentiment analysis and the issues in detecting correct polarity of the texts."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Natural Language Processing, Sentiment Analysis, Social media."}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2021-01-21"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Sentiment Analysis of The Smartphone Product.pdf", "filesize": [{"value": "269 KB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_3", "mimetype": "application/pdf", "size": 269000.0, "url": {"url": "https://meral.edu.mm/record/7702/files/Sentiment Analysis of The Smartphone Product.pdf"}, "version_id": "178f38e1-7cd5-404e-8129-71c05b6c2194"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "Issue 9", "subitem_journal_title": "Sentiment Analysis of the Smart Phone Product Reviews", "subitem_pages": "Pages 56-60", "subitem_volume": "Volume 6"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "May Thandar Theint Aung"}, {"subitem_authors_fullname": "Dr. Aye Aye Kyaw"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Journal article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2018-07-06"}, "item_title": "Sentiment Analysis of the Smart Phone Product Reviews", "item_type_id": "21", "owner": "73", "path": ["1582963674932", "1597396989070"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000007702", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2018-07-06"}, "publish_date": "2018-07-06", "publish_status": "0", "recid": "7702", "relation": {}, "relation_version_is_last": true, "title": ["Sentiment Analysis of the Smart Phone Product Reviews"], "weko_shared_id": -1}