Breath-Group/Covid-Impact-on-AirQuality

The impact of Covid-19 on air quality in Africa using South Africa, Kenya and Nigeria as reference # CovidImpact-AirQuality # Impact of Covid-19 on Air Quality Analysing the impact of the pandemic on Air Quality in 3 African countries: Kenya, Nigeria and South Africa using data from Twitter. Tasks: * **Scraping**: Scraping data related to air quality on the 3 countries from twitter. * **Time series analysis**: Checking for trends and seasonality in the tweets volume, tweeps volume, tweets content et.c. * **Topic Modeling**: Using Latent Dirichlet Allocation for Topic Modeling. * **Sentiment Analysis**: Using Hugging Face Zero Shot ### Project Structure `modeling kernels`contains the following notebook: * EDA_modelling.ipynb - The master notebook that contains all sorts of analysis done right from data preperocessing, EDA, time series analysis, LDA ... NB viewer- its a big notebook `scraping kernels` contains the following notebook: * crawler_tweets.ipynb - Kernel responsible for tweets scraping. * scrap_tweeps.ipynb - Kernel responsible for tweeps scraping. (Using geeotags and hashtag filters.) `licence` License template `readme` Markdown file giving a brief description of the project and its structure. `Covid Impact On Air Quality Rough Document.pdf` First report. May have some corrections to be made. Link to Markdown version `report` Contains the markdown format and the assets of the Document