Pydata Taipei 2020
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Is a Twitter user's location correlated with their opinion on #COVID-19? Presented by CML's student: Anna Chang
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Pydata Taipei 2020
- 1. Is a Twitter user’s location correlated with their opinion on #COVID-19? Rong-Ching Chang Chun-Ming Lai, Assist Prof Information Security Lab X Social Computing And Information Security Lab (SCIS) Tunghai University Twitter@AnnCC12
- 2. Agenda • General introduction of How you get data from Twitter • Data, Data Pre-processing • Mythology • What top 5 countries of English users tweets about during Feb to May • How is it different from getting data from Facebook?
- 3. How do you get data from Twitter Twitter API Hydration Web Scrapping Tools
- 4. Twitter API Twitter Account Twitter Developer Account Create Application
- 5. Open data & Covid & Hydration Citation Dataset from: Umair Qazi, Muhammad Imran, Ferda Ofli. GeoCoV19: A Dataset of Hundreds of Millions of Multilingual COVID-19 Tweets with Location Information. ACM SIGSPATIAL Special, May 2020. doi: https://doi.org/10.1145/3404820.3404823
- 6. Basic Data Pre-processing A -> a @ mail # hashtags https:// @mention Dooing -> doing Doing - > do :$%#@ n, nan stopwords Filter lang Filter geography Remove top 20, tail 20 words Tokenization Word frequency WorldCloud, Trigram
- 8. Word Cloud Word Cloud Word Frequency Categorization Mixed A word cloud is a kind of weighted list to visualize language or text data the size of font indicates the number of subcategories of a collection. the size of font represents the number of keywords that appears in the collection. Cite:Yuping Jin, “Development of Word Cloud Generator Software Based on Python”, GCMM 2016
- 9. N Gram ‘soon’ ‘soon’, ‘Comprehensive’ ‘soon’, ‘Comprehensive’, ‘testing’ 2- Gram Bi-Gram 1- Gram -Gram 3- Gram Tri-Gram
- 10. N Gram ‘released’ ‘charles’ ‘released’, ‘melbourne’ ‘charles’,’test’ ‘released’, ‘melbourne’, ‘immigration’ ‘charles’,’test’,’positive’
- 14. Top 5 Countries (ISO 3166-1 alpha-2) • 'us’ United States of America • ‘in’ India • ‘gb’ United Kingdom • ‘cn’ China • 'au’ Australia • Date • 2/1 • 3/16 • 3/25 • 4/25
- 15. Top 5 Countries Total Tweets
- 16. Top 5 Countries Polarity & Subjective
- 17. United States 2020/02/01 2020/03/16 2020/03/25 2020/04/25
- 18. United States Baltimore protests Freddie Gray's death Odion Jude Ighalo a footballer who played in china
- 20. India
- 21. United Kingdom 2020/03/16 2020/03/25 2020/04/25
- 22. United Kingdom
- 24. China
- 26. Australia
- 27. How do you get data from Facebook A tool from Facebook to help follow, analyze, and report on what’s happening across social media.
- 28. How can you access it? Chrome Extension University researchers
- 29. Crowd Tangle Chrome Extension
- 31. Thank you Rong-Ching Chang Chun-Ming Lai, Assist Prof Information Security Lab X Social Computing And Information Security Lab (SCIS) Tunghai University Twitter@AnnCC12
Hinweis der Redaktion
- 解釋為什麼選四個點 把confirm cases
- Mis spelling Lemmatization Optional common word removal, you can also add stopwords or additional words
- In the categorization type, the size of font indicates the number of subcategories of a collection.
- For the capture of stylometric features, they based their approach on trigrams, arguing that trigrams capture stylometric features well and are more extensible to unknown text when using a small training set, comparing to a bag of words approach. Daniel Ricardo Jaimes Moreno. Et al. “Prediction of Personality Traits in Twitter Users with Latent Features “, IEEE, 2019
- For the capture of stylometric features, they based their approach on trigrams, arguing that trigrams capture stylometric features well and are more extensible to unknown text when using a small training set, comparing to a bag of words approach. Daniel Ricardo Jaimes Moreno. Et al. “Prediction of Personality Traits in Twitter Users with Latent Features “, IEEE, 2019
- The polarity score is a float within the range [-1.0, 1.0] The sentiment polarity can be determined as positive, negative and neutral.
- Subjective 主觀 Objective 客觀 The subjectivity is a float within the range [0.0, 1.0] where 0.0 is very objective and 1.0 is very subjective.
- 'us','in','gb','cn','au’ 解釋為什麼選四個點 把confirm cases
- 'us','in','gb','cn','au'
- In the end of March, you can clearly see the positive sentiment In the end of April 25, covid is clearly being tweeted with some political messages 放number of tweets