Pinned Repositories
amb-node
Node app to interface with the AMB timing system
antics9port
Plan 9 from User Space :: Antics' Acme Modifications
inventoria-node
Distribute, trade, share and care.
node-flattr
NodeJS Flattr API client
Pigeon
A private messenger for Android.
plan9-doc
Qualitative-Analysis-For-Well-Being-Management
Addressing the overall well-being of underserved communities has been a missing part of puzzle in Big Data Science. Every individuals should have an equal opportunity to reach their full potential in every sphere of their life, but reality is far behind this. Since so many individuals lack the opportunity to improve their lifestyle, the expulsion of health disparity has been emerged as a major worldwide public health objective. This project focuses on the analysis of the reasons for the prevalence of these problems in a rural community in India and thus preventing those at low cost and high speed. To unveil this, the content of the text data that has been obtained by conducting surveys and informal interviews, are analyzed using two different approaches: (i) Using Word2Vec which helps in understanding the relevant related keywords from the data and (ii) A Text Classification approach using a simple Artificial Neural Network (ANN), whose result is then visualized using a WordCloud. Textual data contains abundant qualitative information that are not easy to undergo a statistical analysis unlike quantitative data. The findings says that, for our data, the combination of Text Classification with Word2Vec provides more efficient results than using those modeling approaches individually, as it can find niche topics and associated vocabularies from the interview data. This project report provides an overview on the qualitative research, the techniques that are used to analyze our textual data for obtaining meaningful information, the limitations of those approaches and also suggests some possible ways for further study.
sandy
sandy text editor
vaktis.nu
antics's Repositories
antics/node-flattr
NodeJS Flattr API client
antics/sandy
sandy text editor
antics/amb-node
Node app to interface with the AMB timing system
antics/antics9port
Plan 9 from User Space :: Antics' Acme Modifications
antics/inventoria-node
Distribute, trade, share and care.
antics/Pigeon
A private messenger for Android.
antics/plan9-doc
antics/Qualitative-Analysis-For-Well-Being-Management
Addressing the overall well-being of underserved communities has been a missing part of puzzle in Big Data Science. Every individuals should have an equal opportunity to reach their full potential in every sphere of their life, but reality is far behind this. Since so many individuals lack the opportunity to improve their lifestyle, the expulsion of health disparity has been emerged as a major worldwide public health objective. This project focuses on the analysis of the reasons for the prevalence of these problems in a rural community in India and thus preventing those at low cost and high speed. To unveil this, the content of the text data that has been obtained by conducting surveys and informal interviews, are analyzed using two different approaches: (i) Using Word2Vec which helps in understanding the relevant related keywords from the data and (ii) A Text Classification approach using a simple Artificial Neural Network (ANN), whose result is then visualized using a WordCloud. Textual data contains abundant qualitative information that are not easy to undergo a statistical analysis unlike quantitative data. The findings says that, for our data, the combination of Text Classification with Word2Vec provides more efficient results than using those modeling approaches individually, as it can find niche topics and associated vocabularies from the interview data. This project report provides an overview on the qualitative research, the techniques that are used to analyze our textual data for obtaining meaningful information, the limitations of those approaches and also suggests some possible ways for further study.
antics/vaktis.nu
antics/whitebophir
Online collaborative Whiteboard that is simple, free, easy to use and to deploy