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

DRG Description
The Covid-19 pandemic has required us to navigate a challenging 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 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 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).

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.

Week 1:
Key Question: Who are we, what are we trying to do, and how are we going to go about it?

Meeting Agenda
 * Introductions
 * Scope Review
 * Tour and Overview
 * Commitments and communication

After-Meeting To-Do Items
 * Read the project proposal. Think of at least one question.
 * Read our two grounding texts. Write a short answer to the following two questions:
 * What is sensemaking?
 * What is 'institutional provisioning'?

Week 2:
Key Question: What is "sensemaking"? "Institutional provisioning"? And how do these relate to the idea of the "information landscape"?

Meeting Agenda After-Meeting Follow-Up [You will receive feedback on your written summary, including either an "OK" or a "Revise and Resubmit" decision.]
 * Proposal review: what's missing, confusing, or wrong?
 * Your thoughts & writings on theory: does this approach make sense?
 * 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?
 * What setting do they use? What kind of data do they gather?
 * What methods do they use to extract meaning from the data?
 * What conclusions did they draw? Do you believe their conclusions?
 * Can this article help us with our project? How?
 * Prepare to share your article summary with the group.

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

Meeting Agenda After-Meeting Follow-Up
 * Present your summary
 * Content Analysis
 * Research Protocol
 * Trial Run
 * Review research protocol.
 * First round data analysis [due before next meeting]

Week 4:
Key Question: Is our approach working? How might we adjust our protocol based on what we're seeing in the data?

Meeting Agenda
 * Discuss your experience coding data
 * Discuss our agreement levels so far
 * Plan next steps

Week 5:
Continue Content Analysis

Week 6:
Continue Content Analysis

Week 7:
Continue Content Analysis; Begin Data Analysis

Week 8:
Continue Data Analysis

Week 9:
Finalize Analysis and Write Up Progress

Week 10:
Complete Writing Tasks

Finals Week:

 * Revision Task
 * Dissemination Task