Published By: University of Rochester, 2/20/2017

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Summary

Jiebo Luo and Yu Wang are using Twitter data to develop models that would correctly predict the result of the 2016 presidential election. They are analyzing Twitter data from the candidates’ followers with machine learning to identify trends that correlate with events and changes during the campaigns, and with the final results.

Flesch-Kincaid Grade Level of Article: 12

Extended Discussion Questions

• The article discusses some strengths and weaknesses of studying social-media information to gather data for a study, as compared to calling people to survey them.  How does this comparison affect your confidence in one method or the other? Why?
• What are some legal and ethical concerns that could arise from mining public Twitter data for this study?
  • How might mining Twitter posts that have their GPS data attached raise concerns with privacy and security?
• The researchers point out some drawbacks of mining GPS data from a social-media platform, to explain why they did not try to tie user opinions to their location. If they had ignored these drawbacks, how might it have affected their results?
• There are some credibility issues that can affect studies that use information mined from social-media platforms. (For example, not knowing whether a user is an authority on the topic, whether they might be spreading false information, etc.)
  • Do these issues affect the validity of the study described in this article? If so, how? If not, why not?
  • If you were conducting a study that used social-media data, how would you decide whether the credibility of the information in the tweets is important to the validity of your study?

Relating This Story to the CSP Curriculum Framework

Global Impact Learning Objectives:

• LO 7.1.1 Explain how computing innovations affect communication, interaction, and cognition.
• LO 7.3.1 Analyze the beneficial and harmful effects of computing.
• LO 7.4.1 Explain the connections between computing and real-world contexts, including economic, social, and cultural contexts.

Global Impact Essential Knowledge:

• EK 7.1.1C Social media continues to evolve and fosters new ways to communicate.
• EK 7.1.1N The Internet and the Web have changed many areas, including e-commerce, health care, access to information and entertainment, and online learning.
• EK 7.3.1G Privacy and security concerns arise in the development and use of computational systems and artifacts.
• EK 7.3.1J Technology enables the collection, use, and exploitation of information about, by, and for individuals, groups, and institutions.

Other CSP Big Ideas:

• Idea 3 Data and Information

Banner Image: “Network Visualization – Violet – Offset Crop“, derivative work by ICSI. New license: CC BY-SA 4.0. Based on “Social Network Analysis Visualization” by Martin Grandjean. Original license: CC BY-SA 3.0.