tweet sentiment word cloud

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  Landing page on left list of trending topic in twitter with link, on right covid-19 live data,And a search keyword that search from twitter

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  Result of the search keyword, wordcloud for positive,negative sentiment most frequent words

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  Result of the search keyword, wordcloud for neutral sentiment most frequent words and most retweet tweet for search keyword

Inspiration

To know the descriptive word the user use during tweet to define their sentiments.

What it does

The project divides the tweet into three different sentiments and create a wordcloud among them with most frequent used words

How we built it

Building the project for hackathon has been a team work. We got to know teammates before hackathon started. So, we have had good communication about each others skill. I gave a hint of an idea and everyone contributed their skills and idea on building this project.

Challenges we ran into

Accomplishments that we're proud of

We accomplished the target of what we wanted to build. we had good communication among our self. And we get to learn from each other.

What we learned

Working with a team is a benefit in hand. It helped to debug the problem. And learn new skills through work shops and project demand

What's next for tweet sentiment wordcloud

Looking forward for share more ideas and work on it with the team.

Built With

• flask
• https://corona.lmao.ninja/v2/countries
• nltk
• python
• react
• react-tag-cloud
• tweepy
• vadersentimentintensityanalyzer