-
RootNode
-
Co-operative College, Mandalay
-
Cooperative College, Phaunggyi
-
Co-operative University, Sagaing
-
Co-operative University, Thanlyin
-
Dagon University
-
Kyaukse University
-
Laquarware Technological college
-
Mandalay Technological University
-
Mandalay University of Distance Education
-
Mandalay University of Foreign Languages
-
Maubin University
-
Mawlamyine University
-
Meiktila University
-
Mohnyin University
-
Myanmar Institute of Information Technology
-
Myanmar Maritime University
-
National Management Degree College
-
Naypyitaw State Academy
-
Pathein University
-
Sagaing University
-
Sagaing University of Education
-
Taunggyi University
-
Technological University, Hmawbi
-
Technological University (Kyaukse)
-
Technological University Mandalay
-
University of Computer Studies, Mandalay
-
University of Computer Studies Maubin
-
University of Computer Studies, Meikhtila
-
University of Computer Studies Pathein
-
University of Computer Studies, Taungoo
-
University of Computer Studies, Yangon
-
University of Dental Medicine Mandalay
-
University of Dental Medicine, Yangon
-
University of Information Technology
-
University of Mandalay
-
University of Medicine 1
-
University of Medicine 2
-
University of Medicine Mandalay
-
University of Myitkyina
-
University of Public Health, Yangon
-
University of Veterinary Science
-
University of Yangon
-
West Yangon University
-
Yadanabon University
-
Yangon Technological University
-
Yangon University of Distance Education
-
Yangon University of Economics
-
Yangon University of Education
-
Yangon University of Foreign Languages
-
Yezin Agricultural University
-
New Index
-
Item
{"_buckets": {"deposit": "509f76e1-c725-48ad-a875-2275c370bbcc"}, "_deposit": {"created_by": 73, "id": "7783", "owner": "73", "owners": [73], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "depid", "value": "7783"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/00007783", "sets": ["user-miit"]}, "communities": ["miit"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Social Media (Twitter) Data Analysis using Maximum Entropy Classifier on Big Data Processing Framework (Case Study: Analysis of Health Condition, Education Status, States of Business)", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Most of the people aren’t aware about their health situation, and they don’t interest which level has been stand by their nation in case of business and health states. These factors are considered as important things to be improved each nation. Therefore, it is needed to focus these things not only citizens but also the authorities of each country. But, it can be difficult to focus these stated factors without using the modern computer technology. Nowadays, most of the people friendly used social media and people have started expressing their feelings and activities on it. And so, social media is a valuable source to analyze these things by using data mining techniques. Therefore, social media (Twitter) data analysis system is developed to know about health condition, education status, and states of business which are good, fair, or bad based on the data that they post on the Twitter. Maximum Entropy classifier is used to perform sentiment analysis on their tweets to suggest these stated conditions. It is interacting with Twitter data (big data environment), and so, big data processing framework is built to efficiently handle large amount of Twitter data."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Sentiment Analysis, Big Data, Framework, MaxEnt, Twitter"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2021-01-26"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Social Media (Twitter) Data Analysis using Maximum Entropy Classifier on Big Data Processing Framework (Case Study Analysis of Health Condition, Education Status, States of Business).pdf", "filesize": [{"value": "640 KB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_2", "mimetype": "application/pdf", "size": 640000.0, "url": {"url": "https://meral.edu.mm/record/7783/files/Social Media (Twitter) Data Analysis using Maximum Entropy Classifier on Big Data Processing Framework (Case Study Analysis of Health Condition, Education Status, States of Business).pdf"}, "version_id": "fd5e3b22-cdb1-4c98-b2b2-d9f5dcc52062"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "\" Issue 1(2018), E-ISSN: 2278-4136, P-ISSN: 2349-8234, JPP 2018\"", "subitem_journal_title": "Intl. J. of Pharmacognosy and Phytochemistry, UGC Approved (UGC S. No. 45051)", "subitem_pages": "Pages 695-700", "subitem_volume": "Volume 7"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Hein Htet"}, {"subitem_authors_fullname": "Yi Yi Myint"}]}]}, "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": "2018-03-06"}, "item_title": "Social Media (Twitter) Data Analysis using Maximum Entropy Classifier on Big Data Processing Framework (Case Study: Analysis of Health Condition, Education Status, States of Business)", "item_type_id": "21", "owner": "73", "path": ["1582963674932", "1597396989070"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000007783", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2018-03-06"}, "publish_date": "2018-03-06", "publish_status": "0", "recid": "7783", "relation": {}, "relation_version_is_last": true, "title": ["Social Media (Twitter) Data Analysis using Maximum Entropy Classifier on Big Data Processing Framework (Case Study: Analysis of Health Condition, Education Status, States of Business)"], "weko_shared_id": -1}
Social Media (Twitter) Data Analysis using Maximum Entropy Classifier on Big Data Processing Framework (Case Study: Analysis of Health Condition, Education Status, States of Business)
http://hdl.handle.net/20.500.12678/0000007783
http://hdl.handle.net/20.500.12678/00000077833f7cd535-48cf-4d56-a576-f1580b273275
509f76e1-c725-48ad-a875-2275c370bbcc
Publication type | ||||||
---|---|---|---|---|---|---|
Journal article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Social Media (Twitter) Data Analysis using Maximum Entropy Classifier on Big Data Processing Framework (Case Study: Analysis of Health Condition, Education Status, States of Business) | |||||
Language | en | |||||
Publication date | 2018-03-06 | |||||
Authors | ||||||
Hein Htet | ||||||
Yi Yi Myint | ||||||
Description | ||||||
Most of the people aren’t aware about their health situation, and they don’t interest which level has been stand by their nation in case of business and health states. These factors are considered as important things to be improved each nation. Therefore, it is needed to focus these things not only citizens but also the authorities of each country. But, it can be difficult to focus these stated factors without using the modern computer technology. Nowadays, most of the people friendly used social media and people have started expressing their feelings and activities on it. And so, social media is a valuable source to analyze these things by using data mining techniques. Therefore, social media (Twitter) data analysis system is developed to know about health condition, education status, and states of business which are good, fair, or bad based on the data that they post on the Twitter. Maximum Entropy classifier is used to perform sentiment analysis on their tweets to suggest these stated conditions. It is interacting with Twitter data (big data environment), and so, big data processing framework is built to efficiently handle large amount of Twitter data. | ||||||
Keywords | ||||||
Sentiment Analysis, Big Data, Framework, MaxEnt, Twitter | ||||||
Journal articles | ||||||
" Issue 1(2018), E-ISSN: 2278-4136, P-ISSN: 2349-8234, JPP 2018" | ||||||
Intl. J. of Pharmacognosy and Phytochemistry, UGC Approved (UGC S. No. 45051) | ||||||
Pages 695-700 | ||||||
Volume 7 |