Patient's Feedback Platform for Quality of Services via “Free Text Analysis” in Healthcare Industry Article Swipe
Ahthasham Sajid
,
Muhammad Awais
,
Mirza Amir Mehmood
,
Shazia Batool
,
Amir Shahzad
,
Afia Zafar
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.24003/emitter.v8i2.502
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.24003/emitter.v8i2.502
Data analysis of social media posting continues to offer a huge variety of information about the health situation faced by an individual. Social networking or social media websites provide us a wealth of information generated by users in a variety of domains, that generated information are unstructured and unlabeled and are not captured in an exceedingly systematic manner, as info generated is not humanly possible to process due to its size. One traditional way of collecting patients experience is by conducting surveys and questionnaires, as these methods ask fixed questions and are expensive to administer. In this paper, a patient feedback platform (PFP) using free text sentiment analysis is developed to computationally identify and categorize the polarity expressed in a piece of text. Six machine learning latest algorithms have been used as key evaluation for evaluating accuracy of the developed (PFP) model. Results achieved have shown 88 % accuracy on the basis of which it is recommended that developed (PFP) patient feedback platform could be used to improve E-health care services indeed.
Related Topics
Concepts
Variety (cybernetics)
Categorization
Computer science
Process (computing)
Social media
Sentiment analysis
Quality (philosophy)
Data science
Health care
Key (lock)
Ask price
Knowledge management
World Wide Web
Artificial intelligence
Business
Computer security
Political science
Finance
Epistemology
Law
Philosophy
Operating system
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.24003/emitter.v8i2.502
- https://emitter.pens.ac.id/index.php/emitter/article/download/502/200
- OA Status
- gold
- Cited By
- 2
- References
- 8
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3094033945
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3094033945Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.24003/emitter.v8i2.502Digital Object Identifier
- Title
-
Patient's Feedback Platform for Quality of Services via “Free Text Analysis” in Healthcare IndustryWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-10-23Full publication date if available
- Authors
-
Ahthasham Sajid, Muhammad Awais, Mirza Amir Mehmood, Shazia Batool, Amir Shahzad, Afia ZafarList of authors in order
- Landing page
-
https://doi.org/10.24003/emitter.v8i2.502Publisher landing page
- PDF URL
-
https://emitter.pens.ac.id/index.php/emitter/article/download/502/200Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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-
https://emitter.pens.ac.id/index.php/emitter/article/download/502/200Direct OA link when available
- Concepts
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Variety (cybernetics), Categorization, Computer science, Process (computing), Social media, Sentiment analysis, Quality (philosophy), Data science, Health care, Key (lock), Ask price, Knowledge management, World Wide Web, Artificial intelligence, Business, Computer security, Political science, Finance, Epistemology, Law, Philosophy, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
8Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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