Directed Research Group: The COVID-19 Information Landscape (Fall 2020): Difference between revisions

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===DRG Description===
===DRG Description===
The Covid-19 pandemic has required us to navigate a challenging
The Covid-19 pandemic has required us to navigate a challenging information landscape. How have our institutions responded, and how have people made sense of the information provided to them? What role have search platforms played in shaping this terrain?  
information landscape. How have our institutions responded to this
challenge, and how have people made sense of the information provided
to them? What role have search platforms played in shaping this
challenging terrain? In this Directed Research Group, you'll learn and
apply theories of sensemaking and institutional provisioning to
conduct a content analysis on search engine results collected during
the pandemic. We'll analyze the data you collect and reflect on what
this can tell us about our response to the crisis. Together, we'll
develop a research paper for publication and share our insights with
the broader community. Alternatively, you may choose to develop your
own project in the supportive environment of our DRG, perhaps
including data from other sources we have collected such as Wikipedia,
Reddit, and Twitter.


Strong reading and writing skills in the English language, a computer
In this Directed Research Group, you'll conduct a content analysis on search engine results collected during the pandemic. The group will be run for 3-5 excellent students interested in engaging in faculty directed research. The research group will be organized by the Community Data Science Collective by Benjamin Mako Hill and Kaylea Champion and will be conducted for UW course credit. We'll analyze the data you collect and reflect on what it can tell us about our response to the crisis.  
you can use during the project, ability to attend team meetings
through an online conferencing platform, and a commitment to
high-quality results are required. Willingness to work both in a team
and independently is required. Familiarity with research practices,
content analysis, R, and Python are helpful but not required.


To join this DRG, submit a resume and/or cover letter (the resume
Prerequisites: Strong reading and writing skills in the English language, a computer you can use during the project, ability to attend team meetings through an online conferencing platform, and a commitment to high-quality results are required. Willingness to work both in a team and independently is required. We strongly prefer candidates with experience in social scientific research methods (such as COM 301). Familiarity with content analysis, R, and Python are all helpful but not required.
might contain a brief list of recent courses and any relevant work
 
experience, the cover letter could be a description of why you'd like
Applying: To apply to join this DRG, submit a cover letter and resume to covid-drg@communitydata.science. The resume might contain a brief list of recent courses and any relevant work experience, the cover letter could be a description of why you'd like to participate, including your academic or career interests, or what you hope to learn.  If selected, you will be able to enroll for 4-5 credits, depending on how much time you can commit to the project (for 4 credits, you commit 12 hours, for 5 credits, you commit 15 hours per week).
to participate, including your academic or career interests, or what
you hope to learn).


===DRG Responsibilities and Commitments===
===DRG Responsibilities and Commitments===
As a DRG member, you are joining an active research project, and you are expected to learn both through information presented to you as well as through your own initiative. What you get out of this project will match what you put into it. Communication is essential to keep our collaboration smooth, and your commitment to doing good quality work is essential. We are trying to develop knowledge that will be useful to the public, and that means holding ourselves to maximum standards of accuracy and ethics. Be honest and open about what you do and always do your best: life happens to all of us and we live in interesting times. Work that's a little late is understandable especially if you communicate early and often, but work that's not your best effort can't be accepted.
As a DRG member, you are joining an active research project, and you are expected to learn both through information presented to you as well as through your own initiative. What you get out of this project will match what you put into it. Communication is essential to keep our collaboration smooth, and your commitment to doing good quality work is essential. We are trying to develop knowledge that will be useful to the public, and that means holding ourselves to maximum standards of accuracy and ethics. Be honest and open about what you do and always do your best: life happens to all of us and we live in interesting times. Work that's a little late is understandable especially if you communicate early and often, but work that's not your best effort can't be accepted.
===Key Text===
Available for free from the UW Library: https://dx-doi-org.offcampus.lib.washington.edu/10.4135/9781071802878


===DRG Schedule===
===DRG Schedule===
====Week 1: ====
====Week 1: ====
Key Question: Who are we, what are we trying to do, and how are we going to go about it?
Key Question: Who are we, what are we trying to do, and how are we going to go about it?
'''Preparation'''
* Read the project outline. Come with questions!


'''Meeting Agenda'''
'''Meeting Agenda'''
* Introductions
* Introductions
* Scope Review
* Scope Review
* Tour and Overview
* Tour and Overview of the Data
* Commitments and communication
* Important Issue: Qualitative versus Quantitative (Example: "Has September in Seattle been dreary and miserable?")
* Content Analysis: What is it?
* Commitments and communication ++ time tracking


'''After-Meeting To-Do Items'''
'''After-Meeting To-Do Items'''
* Read the project proposal. Think of at least one question.
Read the first two parts of this multipart article about how Google works:
* Read our two grounding texts. Write a short answer to the following two questions:
* https://computer.howstuffworks.com/internet/basics/google.htm and
** What is sensemaking?
* https://computer.howstuffworks.com/internet/basics/google1.htm
** What is 'institutional provisioning'?
 
For a more critical view of algorithms and online platforms, please read:
* https://www.kqed.org/education/532002/youtube-algorithms-how-to-avoid-the-rabbit-hole
* https://points.datasociety.net/your-data-is-being-manipulated-a7e31a83577b
8 https://internethealthreport.org/2019/your-mobile-apps-are-tracking-you/
* First sample: Dive In! Write up your thoughts as you look through the two types of data we'll look at: lists of top searches, and images of covid-19 and coronavirus searches.
* Read through page 22 of Kaylea's [[https://docs.google.com/document/d/1rMdD-JtwQ5uKtfQ2uIQpBv8ymUluvPHAtjFoQC0I4ps/edit?usp=sharing|annotated version of Braun and Clark 2006]] -- note that there are both highlighted areas and comments. You may need to adjust your view so you can see the sidebar with comments. Feel free to add your own notes and questions for everyone to benefit.


====Week 2:====
====Week 2:====
Key Question: What is "sensemaking"? "Institutional provisioning"? And how do these relate to the idea of the "information landscape"?
Key Questions: What are your initial impressions of this data? What do Braun and Clark say about how can we turn those initial impressions into knowledge?


'''Meeting Agenda'''
'''Meeting Agenda'''
* Proposal review: what's missing, confusing, or wrong?
* Your sample: what trends did you see? Let's talk about the data!
* Your thoughts & writings on theory: does this approach make sense?
* Walk through Braun and Clark.
 
'''After-Meeting Follow-Up'''
'''After-Meeting Follow-Up'''
* Article summary: one paragraph about your chosen article, answering the following questions:
 
** What research question is the author trying to answer, or what hypothesis are they trying to test?
* Let's dive into the data and start on Braun and Clark's phase 1 and 2. This is codes development round 1.
** What setting do they use? What kind of data do they gather?
* Make notes on everything as you go.
** What methods do they use to extract meaning from the data?
* Visit each item in your sample for phase 1, and then again for phase 2.  
** What conclusions did they draw? Do you believe their conclusions?
* Reflect on what you've seen so far.
** Can this article help us with our project? How?
* Prepare to share your article summary with the group.
[You will receive feedback on your written summary, including either an "OK" or a "Revise and Resubmit" decision.]


====Week 3:====
====Week 3:====
Key Question: What have others done related to this topic? How will we analyze this data?
Key Question: What are we seeing in this data?


'''Meeting Agenda'''
'''Meeting Agenda'''
* Present your summary
* Research Protocol -- what's coming up next?
* Content Analysis
* Open codes discussion: what did you see?
* Research Protocol
 
* Trial Run
'''After-Meeting Follow-Up'''
'''After-Meeting Follow-Up'''
* Review research protocol.  
* Braun & Clark phases 1&2 for a new set of data. This is codes development round 2.
* First round data analysis [due before next meeting]
* Do your previous codes still work? Will you incorporate ideas from colleagues?


====Week 4:====
====Week 4:====
Key Question: Is our approach working? How might we adjust our protocol based on what we're seeing in the data?
Key Question: Is this working? Can we make a codebook out of what we've seen?
 
'''Meeting Agenda'''
* Share your codes so far
* Codebook production discussion
* Prep for next phase.
 
'''After-Meeting Follow-Up'''
* Read pp. 1-2, 18-34 of Ch 1 of the online version of Neuendorf
 
====Week 5:====
Key Question: Does this codebook make sense?
 
'''Meeting Agenda'''
* Codebook presentation, discussion, training.
* Synchronized coding + discussion
 
'''After-Meeting Follow-Up'''
* Read Neuendorff, Ch 2., pp. 36-44, and Ch 3. pp 70-84. Skim the rest of Ch3.
* This is Pilot Round 1, and we are entity coding for agreement
 
====Week 6:====
Key Question: Is this working?


'''Meeting Agenda'''
'''Meeting Agenda'''
* Discuss your experience coding data
* Discuss your experience coding data
* Discuss our agreement levels so far
* Discuss our agreement levels so far
* Plan next steps
* Update codebook as needed
 
'''After-Meeting Follow-Up'''
* Read Neuendorff p. 139-166.
* This is Pilot Round 2, and we are entity coding for agreement


====Week 5:====
'''Continue Content Analysis'''
====Week 6:====
'''Continue Content Analysis'''
====Week 7:====
====Week 7:====
'''Continue Content Analysis; Begin Data Analysis'''
Key Question Still Is: Is this working?
 
'''Meeting Agenda'''
* Discuss your experience coding data
* Discuss our agreement levels so far
* Update codebook as needed
 
'''Follow-up Items'''
* Read Neuendorff p.169-206
* If Agreement is sufficiently high, this is when we Begin independent coding


====Week 8:====
====Week 8:====
'''Continue Data Analysis'''
'''Meeting Agenda'''
====Week 9:====
* Discuss coding progress
'''Finalize Analysis and Write Up Progress'''
 
'''Follow-Up Items'''
* Keep Coding
* Read Neuendorff p. 221-230, 234-248 (through just the first paragraph)
 
====Week 9====
 
'''Meeting Agenda'''
* Discuss coding progress
 
'''Follow-Up Items'''
* Keep Coding
* Read Neuendorf p. 334-340, 394-403
 
====Week 10:====
====Week 10:====
'''Complete Writing Tasks'''
'''Complete Writing and Coding Tasks'''
 
====Finals Week:====
====Finals Week:====
*Revision Task
*Revision Task
*Dissemination Task
*Dissemination Task

Revision as of 23:34, 18 September 2020

DRG Description

The Covid-19 pandemic has required us to navigate a challenging information landscape. How have our institutions responded, and how have people made sense of the information provided to them? What role have search platforms played in shaping this terrain?

In this Directed Research Group, you'll conduct a content analysis on search engine results collected during the pandemic. The group will be run for 3-5 excellent students interested in engaging in faculty directed research. The research group will be organized by the Community Data Science Collective by Benjamin Mako Hill and Kaylea Champion and will be conducted for UW course credit. We'll analyze the data you collect and reflect on what it can tell us about our response to the crisis.

Prerequisites: Strong reading and writing skills in the English language, a computer you can use during the project, ability to attend team meetings through an online conferencing platform, and a commitment to high-quality results are required. Willingness to work both in a team and independently is required. We strongly prefer candidates with experience in social scientific research methods (such as COM 301). Familiarity with content analysis, R, and Python are all helpful but not required.

Applying: To apply to join this DRG, submit a cover letter and resume to covid-drg@communitydata.science. The resume might contain a brief list of recent courses and any relevant work experience, the cover letter could be a description of why you'd like to participate, including your academic or career interests, or what you hope to learn. If selected, you will be able to enroll for 4-5 credits, depending on how much time you can commit to the project (for 4 credits, you commit 12 hours, for 5 credits, you commit 15 hours per week).

DRG Responsibilities and Commitments

As a DRG member, you are joining an active research project, and you are expected to learn both through information presented to you as well as through your own initiative. What you get out of this project will match what you put into it. Communication is essential to keep our collaboration smooth, and your commitment to doing good quality work is essential. We are trying to develop knowledge that will be useful to the public, and that means holding ourselves to maximum standards of accuracy and ethics. Be honest and open about what you do and always do your best: life happens to all of us and we live in interesting times. Work that's a little late is understandable especially if you communicate early and often, but work that's not your best effort can't be accepted.

Key Text

Available for free from the UW Library: https://dx-doi-org.offcampus.lib.washington.edu/10.4135/9781071802878

DRG Schedule

Week 1:

Key Question: Who are we, what are we trying to do, and how are we going to go about it?

Preparation

  • Read the project outline. Come with questions!

Meeting Agenda

  • Introductions
  • Scope Review
  • Tour and Overview of the Data
  • Important Issue: Qualitative versus Quantitative (Example: "Has September in Seattle been dreary and miserable?")
  • Content Analysis: What is it?
  • Commitments and communication ++ time tracking

After-Meeting To-Do Items Read the first two parts of this multipart article about how Google works:

For a more critical view of algorithms and online platforms, please read:

8 https://internethealthreport.org/2019/your-mobile-apps-are-tracking-you/

  • First sample: Dive In! Write up your thoughts as you look through the two types of data we'll look at: lists of top searches, and images of covid-19 and coronavirus searches.
  • Read through page 22 of Kaylea's [version of Braun and Clark 2006] -- note that there are both highlighted areas and comments. You may need to adjust your view so you can see the sidebar with comments. Feel free to add your own notes and questions for everyone to benefit.

Week 2:

Key Questions: What are your initial impressions of this data? What do Braun and Clark say about how can we turn those initial impressions into knowledge?

Meeting Agenda

  • Your sample: what trends did you see? Let's talk about the data!
  • Walk through Braun and Clark.

After-Meeting Follow-Up

  • Let's dive into the data and start on Braun and Clark's phase 1 and 2. This is codes development round 1.
  • Make notes on everything as you go.
  • Visit each item in your sample for phase 1, and then again for phase 2.
  • Reflect on what you've seen so far.

Week 3:

Key Question: What are we seeing in this data?

Meeting Agenda

  • Research Protocol -- what's coming up next?
  • Open codes discussion: what did you see?

After-Meeting Follow-Up

  • Braun & Clark phases 1&2 for a new set of data. This is codes development round 2.
  • Do your previous codes still work? Will you incorporate ideas from colleagues?

Week 4:

Key Question: Is this working? Can we make a codebook out of what we've seen?

Meeting Agenda

  • Share your codes so far
  • Codebook production discussion
  • Prep for next phase.

After-Meeting Follow-Up

  • Read pp. 1-2, 18-34 of Ch 1 of the online version of Neuendorf

Week 5:

Key Question: Does this codebook make sense?

Meeting Agenda

  • Codebook presentation, discussion, training.
  • Synchronized coding + discussion

After-Meeting Follow-Up

  • Read Neuendorff, Ch 2., pp. 36-44, and Ch 3. pp 70-84. Skim the rest of Ch3.
  • This is Pilot Round 1, and we are entity coding for agreement

Week 6:

Key Question: Is this working?

Meeting Agenda

  • Discuss your experience coding data
  • Discuss our agreement levels so far
  • Update codebook as needed

After-Meeting Follow-Up

  • Read Neuendorff p. 139-166.
  • This is Pilot Round 2, and we are entity coding for agreement

Week 7:

Key Question Still Is: Is this working?

Meeting Agenda

  • Discuss your experience coding data
  • Discuss our agreement levels so far
  • Update codebook as needed

Follow-up Items

  • Read Neuendorff p.169-206
  • If Agreement is sufficiently high, this is when we Begin independent coding

Week 8:

Meeting Agenda

  • Discuss coding progress

Follow-Up Items

  • Keep Coding
  • Read Neuendorff p. 221-230, 234-248 (through just the first paragraph)

Week 9

Meeting Agenda

  • Discuss coding progress

Follow-Up Items

  • Keep Coding
  • Read Neuendorf p. 334-340, 394-403

Week 10:

Complete Writing and Coding Tasks

Finals Week:

  • Revision Task
  • Dissemination Task