Covidanalysis

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  Website

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  Website

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  Word Cloud

Inspiration

We all want to better understand the information available about COVID-19 by analyzing Twitter feeds of Countries having the most cases(USA). This will help others because they can use this with current Twitter feeds to see trends and important topic words. Also, we have made a dashboard for coronavirus spread across the world. It also provides visionary visualization for spread across the world. Also precaution measure and covid-19 related news and information

What it does

I am using a sample collection of tweets related Coronavirus from the United States. Visualization of word frequency in a given text as a weighted list. The technique has recently been popularly used to visualize the topical content of political speeches. I looked at important categories of words in the word cloud to see what categories of things people are tweeting about. We also looked for negative and positive words to get an idea of sentiment. I presented our word cloud along with resources about coronavirus and how to stay healthy. I also create a website that helped people to see spread analysis across the world.

How we built it

By using Flask and Python and some pre Knowledge of ML and Data Visualization.

Challenges we ran into

I created a website that includes information about COVID-19. I wanted visitors to be able to learn about different things related to COVID-19 in one easy to navigate site. Information about social distancing might help visitors be safe. A number of cases around the world would also help them.

Accomplishments that we're proud of

Categories: There are a few categories of words that appear throughout the word cloud. One category is words related to being sick like tests, sick, and virus spread. Another category is words related to being away from home like closed and travel. There are also several references to money, which may have to do with the economic ramifications of coronavirus.

Sentiment: There appear to be more negative words than positive words in the cloud. Words like serious, alert, and kills are prominent. There are some positive words like temporary and immune, but they are smaller and there are less of them.

What we learned

In conclusion, I found that many of the words could be related to daily life with Coronavirus. Also, I can do add-ons to help people by making a more responsive Website.

What's next for Covidanalysis

I will add an API for the word cloud so it makes it easy for any date analysis and too for real-time. Also, I will add real-time data through API/or use web scraping to scrape data itself from the trusted websites of respective countries instead of sample one to give more real-time updates of covid-19 spread. Also, I will add active cases and chatbot features to the Website.

Built With

• ai
• analysis
• flask
• folium
• heroku
• machine-learning
• pandas
• python