{"_buckets": {"deposit": "5fe68b72-b723-4228-8037-1b9ce688e857"}, "_deposit": {"id": "4812", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4812"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4812", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Sentiment Analysis for Twitter Stream Data by Combining Lexicon and Machine Learning Approaches", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Nowadays, Twitter Sentiment analysis hasbecome popular as it helps the organization todetermine marketing strategy by providing publicopinions. Efficient techniques to collect a large amountof Twitter stream data and extracting sentimentinformation from collected raw data are essentialdemand. Traditional sentiment classificationtechniques do not perform well in Social Data.Acquiring effective training data is a challengealthough learning based approaches are good forSocial Data Sentiment Classification. Manual Labelingfor training data is time and labor consuming. In thispaper, Sentiment Analysis System for Twitter data isproposed with five modules: Data Collection,Preprocessing, Class Labeling, Classification ModelDevelopment and Sentiment Classification. TheSentiment Classification is implemented by combininglexicon and Supervised learning-based approaches. Inthis system, lexicon-based classifier is applied to labelthe class and suitable learning-based classifier ischosen for classification. Emoticon and slang wordsare considered for classification. To select suitableclassifier, three different classification algorithms areevaluated. The performance evaluation shows thatNaïve Bayes classifier is better and the proposedsystem can achieved the promising accuracy."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Sentiment Analysis"}, {"interim": "Social Media data"}, {"interim": "Twitter"}, {"interim": "SentiStrength"}, {"interim": "Machine Learning"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value": []}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Fifteenth International Conference on Computer Applications(ICCA 2017)", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Chan, Wint Nyein"}, {"subitem_authors_fullname": "Thein, Thandar"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2017-02-17"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/709"}, "item_title": "Sentiment Analysis for Twitter Stream Data by Combining Lexicon and Machine Learning Approaches", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004812", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-11"}, "publish_date": "2019-07-11", "publish_status": "0", "recid": "4812", "relation": {}, "relation_version_is_last": true, "title": ["Sentiment Analysis for Twitter Stream Data by Combining Lexicon and Machine Learning Approaches"], "weko_shared_id": -1}