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README.md
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# How world reacted to Coronavirus Case Study
URL of case study is https://coronacase-study.herokuapp.com/
# This case-study answers following questions:
- Is hate speech or offensive language or both are involved?
- To whom hate speech were directed to?
- Can we identify the main abusers on twitter?
- Temporal Analysis?
- Variation in Emotions?
- Any other finding evident from large volume of twitter data?
# This case study studies the impact of:
1. Hate speech: abusive or threatening speech or writing that expresses prejudice against a particular group, especially on the basis of race, religion, or sexual orientation.
2. Offensive tweets: insulting, unpleasant, disgusting, abusive language, as to the senses causing anger or annoyance.
3. Sentiment scores: It determines whether a piece of text is positive, negative or neutral.
4. Mean sentiment scores: It is the average/mean of sentiment scores of the tweets posted over the period of one month to determine overall positivity or negativity in tweets of the respective month.
# Methodology
After collection of tweets these were labelled offensive, hate speech and sentiment scores were annotated.
For creating word cloud the offensive, hate speech tweets were pre-processed using regular expressions in python, then for stop words removal tweets were passed into 'en_core_web_sm' module of Spacy library for removal and filtering out stop words.
# Dataset Details
Hashtags | Tweets collected | Corresponding hashtags | Start Date | End Date
------------ | ------------- | ------------- | ------------- | ------------- |
Coronavirus | 13939 | #coronavirus | 1 November 2019 | 30 May 2020
Coronavirusinindia | 4769 | #Coronavirusinindia | 1 November 2019 | 30 May 2020
Covid19 | 9690 | #Covid19 | 1 November 2019 | 30 May 2020
Coronavirusoutbreak | 6611 | #Coronavirusoutbreak | 1 November 2019 | 30 May 2020
Coronaviruschina | 5358 | #Coronaviruschina | 1 November 2019 | 30 May 2020
coronaviruspandemic | 4858 | #coronaviruspandemic | 1 November 2019 | 30 May 2020
coronavirussucks | 2506 | #coronavirussucks | 1 November 2019 | 30 May 2020
coronavirusitalianews | 3776 | #coronavirusitalianews | 1 November 2019 | 30 May 2020
racistcorona | 18 | #racistcorona | 1 November 2019 | 30 May 2020