Summary
Chapters
Video Info
Summary
Samira Shaikh, PhD, Assistant Professor in Cognitive Science at the University of North Carolina, discusses her research of machine learning to understand solidarity and emoji use on social media, including skills needed to for both social science and computer science; collection of solidarity data; collection, management, and cleaning of Twitter data; the importance of emojis; challenges faced and overcome; working with social media in different languages; results of the research; aspects requiring further research; and advice for students conducting similar research.
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Chapter 1: How did You Become Interested in Studying Artificial Intelligence?
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Chapter 2: What Skills do You Utilize to Bridge the Gap Between Computer Science and Social Science?
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Chapter 3: What Recent Research Have You Undertaken Using Computational Methods?
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Chapter 4: Where did You Collect Your Data From, and Which Events Were You Focusing on to Study Solidarity?
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Chapter 5: How did You Gather the Twitter Data?
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Chapter 6: How did You Start to Sort Through the Data and What did you Notice?
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Chapter 7: How did You Ensure That You Removed any Data You did not Need to Analyze?
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Chapter 8: How Important are Emoji in Characterizing Human Behavior in Online Social Networks?
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Chapter 9: What Challenges did You Face During the Project, and how did You Overcome Them?
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Chapter 10: How do You Work With Social Media Data in Different Languages?
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Chapter 11: Were There any Surprising Findings Resulting From the Research?
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Chapter 12: Are There any Aspects From the Project That You Would Like to Investigate in Further Research?
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Chapter 13: What Advice do You Have for Students Conducting Similar Research?
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