Social media sentiment study on COVID-19 outbreak
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
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Brac University
2021
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10361-149742022-01-26T10:23:19Z Social media sentiment study on COVID-19 outbreak Karmaker, Anik Hafiz, Nayeem Mohammad Chanda, Anir Akhond, Mostafijur Rahman Department of Computer Science and Engineering, Brac University COVID19 corona virus Twitter tweets Job Education Medical TextBlob Matplotlib Tweepy Natural Language Processing Sentiment analysis Text Polarity COVID-19 (Disease) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 29-31). On 11th March 2020, the World Health Organization announced the COVID19 outbreak as a pandemic. Starting from China, this virus has infected and killed thousands of people from Italy, Spain, the USA, Iran, and other European countries as well. While this pandemic has continued to affect the lives of millions, several countries have resorted to complete lockdown. During this lockdown, people have taken social networks to express their feelings and find a way to calm themselves down. For accurate measurement of awareness of the people, it is necessary to successfully categorize the dataset of social media. The objective of this study is to use different data from twitter and filter these data for awareness measurement and to develop a model for evaluating the awareness among the people of all around the world by analyzing the collected social media opinions. In this research work, we have collected the data in a JSON file format and extracted the data into various criteria. We will parse the JSON file format data to the CSV file format and clean the data to use in our model. We will take English language-based data only. Then we will use the algorithm TextBlob to analyze the social media sentiment. We will finally apply that method to determine the awareness among the people and analyze that they are taking this pandemic very seriously or not. We will also analyze the graphical representation of our special keyword dataset. The result indicates that the methodology can be used to determine people’s awareness and give us an idea about the sentimental issues of people. It will also help the government to take necessary steps for example psychological campaign, counseling program to make the people stronger to handle any pandemic. Anik Karmaker Nayeem Mohammad Hafiz Anir Chanda B. Computer Science 2021-09-05T10:12:12Z 2021-09-05T10:12:12Z 2021 2021-06 Thesis ID 17101294 ID 17101244 ID 17301121 http://hdl.handle.net/10361/14974 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 31 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
COVID19 corona virus Twitter tweets Job Education Medical TextBlob Matplotlib Tweepy Natural Language Processing Sentiment analysis Text Polarity COVID-19 (Disease) |
| spellingShingle |
COVID19 corona virus Twitter tweets Job Education Medical TextBlob Matplotlib Tweepy Natural Language Processing Sentiment analysis Text Polarity COVID-19 (Disease) Karmaker, Anik Hafiz, Nayeem Mohammad Chanda, Anir Social media sentiment study on COVID-19 outbreak |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. |
| author2 |
Akhond, Mostafijur Rahman |
| author_facet |
Akhond, Mostafijur Rahman Karmaker, Anik Hafiz, Nayeem Mohammad Chanda, Anir |
| format |
Thesis |
| author |
Karmaker, Anik Hafiz, Nayeem Mohammad Chanda, Anir |
| author_sort |
Karmaker, Anik |
| title |
Social media sentiment study on COVID-19 outbreak |
| title_short |
Social media sentiment study on COVID-19 outbreak |
| title_full |
Social media sentiment study on COVID-19 outbreak |
| title_fullStr |
Social media sentiment study on COVID-19 outbreak |
| title_full_unstemmed |
Social media sentiment study on COVID-19 outbreak |
| title_sort |
social media sentiment study on covid-19 outbreak |
| publisher |
Brac University |
| publishDate |
2021 |
| url |
http://hdl.handle.net/10361/14974 |
| work_keys_str_mv |
AT karmakeranik socialmediasentimentstudyoncovid19outbreak AT hafiznayeemmohammad socialmediasentimentstudyoncovid19outbreak AT chandaanir socialmediasentimentstudyoncovid19outbreak |
| _version_ |
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