Language Analysis through Tweets

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dla (28)
Use text analysis to compare a collection of tweets in two conditions to draw conclusions about the content or style of communication in these contexts.


By Week 1: Divide the class into 3 large groups, and create group homepages on Canvas in the course. Post directions to Lexos and a sample text file (concatenated Moby Dick and Pride and Prejudice).
By Week 3: Students access and play with the software using the provided sample text file. Brainstorm as a group on the Canvas group homepage about research questions related to the content or style of language that could be addressed through an analysis of tweets.
By Week 5: Work with instructor to finalize research question and identify data set.
By Week 8: Instructor and students work with tech fellows to run Mark LeBlanc's script that will pull and concatenate 500 tweets. Tweets can be collected by time (between a set of specified dates), by the person tweeting, by location (people tweeting near you, or in specific parts of the country), or by search term (hashtag or keyword) -- depending on what is appropriate for the overall research question.
By Week 12: Each student queries the data set using Lexos and posts one graphical output of their analysis on their group homepage on Canvas.
By Week 15 (last day of class): Each student will submit a 2-page paper.
  • Page 1: Interpret at least 2 of the graphs generated by any member of your group. What do they show? What can you conclude about the research question from the graphs?
  • Page 2:Use the implications of these findings to describe a follow up question you would study next. Propose the fantasy data set and analysis you would need to address this question. It does not have to involve an analysis of tweets, but does need to involve the analysis of written or spoken language/communication.

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PSY323 Stress and Illness, Fall 2017

aalbers (4)
dla (28)


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