Self-Quantified is a Community website of self-trackers, self-researchers interested in personal science. It encourages all types of researches to post about their research, ask for advices and explore different methods of self-tracking through wearables.
- Posts by categories with various tags; ‘data’, ‘tools’, ‘diet’, ‘conference’, ‘food’…
If you want to have closer look to the results click INTERACTIVE DASHBOARD HERE
Please install the project dependencies run pip install -r requirements.txt
$ pip install -r requirements.txt
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2nd Please install Pycharm , you can choose PyCharm Community Edition, it's free.
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3rd CE example: run on Pycharm terminal:
$ streamlit run webapp/app.py
- The aim of this project is working to understand the community forum by conducting Data Analysis and Natural Language Processing (NLP) of the community’ interactions.
- Providing transparent analysis of the human behaviour in communication and their patterns of networking to improve occurring and future projects in community and personal science.
- Clustering PCA Model showing type of user engagement
- LDA MODEL, Topic Modelling showing different posts topics
- Named Entity Recognition, products, organisation, person
- Text Classification
- Network Social Analysis graph
- Platform: Python, CorTexT Platform, Pycharm, GEPHI-0.9.2 software for network analysis.
- PythonLibraries used for pre-processing data: NLTK, SPACY, GENISM.
- Libraries for modelling, data viz plLDAvis, sklearn, matplotlib, wordcloud, plotly, seaborn, requests, beautiful soup