Internet Research Methods (Spring 2016)

Designing Internet Research

COM528 - Department of Communication, University of Washington

Instructor: Benjamin Mako Hill (University of Washington)

Course Websites:

• We will use Canvas for announcements, turning in assignments, and discussion
• Everything else will be linked on this page.

Course Catalog Description:

Focuses on designing Internet research, assessing the adaptation of proven methods to Internet tools and environments, and developing new methods in view of particular capacities and characteristics of Internet applications. Legal and ethical aspects of Internet research receive ongoing consideration.

Overview and Learning Objectives

What new lines of inquiry and approaches to social research are made possible and necessary by the Internet? In what ways have established research methods been affected by the Internet? How does the Internet challenge established methods of social research? How are researchers responding to these challenges?

These are some of the key questions we will explore in this course. The course will focus on assessing the incorporation of Internet tools in established and emergent methods of social research, the adaptation of social research methods to study online phenomena, and the development of new methods and tools that correspond with the particular capacities and characteristics of the Internet. The readings will include both descriptions of Internet-related research methods with an eye to introducing skills and examples of studies that use them.The legal and ethical aspects of Internet research will receive ongoing consideration throughout the course. The purpose of this course is to help prepare students to design high quality research projects that use the Internet to study online communicative, social, cultural, and political phenomena.

I will consider the course a complete success if every student is able to do all of these things at the end of the quarter:

• Discuss and compare distinct types of Internet research including: web archiving; textual analysis; ethnography; interviews; network analyses of social and hyperlink networks; analysis of digital trace data, traditional, natural, and field experiments; design research; interviewing; survey research; and narrative and visual analyses.
• Describe particular challenges and threats to research validity associated with each method.
• For at least one method, be able to provide a detailed description of a research project and feel comfortable embarking on a formative study using this methodology.
• Given a manuscript (e.g., in the context of a request for peer review), be able to evaluate a Internet-based study in terms of its use its methodological choices.
• Use a modern programming language (e.g., Python) to collect a dataset from a web API like the APIs from Twitter and Wikipedia.

Note About This Syllabus

You should expect this syllabus to be a dynamic document and you will notice that there are a few places marked "To Be Determined." Although the core expectations for this class are fixed, the details of readings and assignments will shift. As a result, there are three important things to keep in mind:

1. Although details on this syllabus will change, I will not change readings or assignments less than one week before they are due. If I don't fill in a "To Be Determined" one week before it's due, it is dropped. If you plan to read more than one week ahead, contact me first.
2. Closely monitor your email or the announcements section on the course website on Canvas. When I make changes, these changes will be recorded in the history of this page so that you can track what has changed and I will summarize these changes in an announcement on Canvas that will be emailed to everybody in the class.
3. I will ask the class for voluntary anonymous feedback frequently — especially toward the beginning of the quarter. Please let me know what is working and what can be improved. In the past, I have made many adjustments based on this feedback.

Books

This book has no textbook and I am not requiring you to buy any books for this class. That said, several required readings and many suggested readings, will come from several excellent books which you should consider purchasing for your library.

These books include:

1. Rogers, R. (2013). Digital Methods. Cambridge, Massachusetts: The MIT Press.
2. Hesse-Biber, S. N. (Ed.). (2011). The Handbook of Emergent Technologies in Social Research (1st edition). New York: Oxford University Press.
3. Ackland, R. (2013). Web Social Science. SAGE Publications Ltd.

Technical Skills

Nearly all of our structured in-person meetings and all of our readings will focus on teaching conceptual skills related to Internet research. These skills involve the "softer" skills of understanding, designing, and critiquing research plans. These are harder to teach, evaluate, and learn but are ultimately what will make a research project interesting, useful, or valid. When the course has been taught in the past by other faculty, it has been entirely focused on these types of conceptual skills.

That said, I also believe that any skilled Internet researcher must be comfortable writing code to collect a dataset from the web or, at the very least, should have enough experience doing so that they know what is involved and what is possible and impossible. This is essential even if your only goals is to manage somebody else writing code and gathering data. As a result, being successful in this class will also require technical skills.

Because students are going to come to the class with different technical skillsets, we well be devoting a relatively small chunk of class time to developing technical skills. Instead, I'm requiring that students build these skills outside of the class if they do not have them already.

In particular, I want every student to have the following three things:

1. Basic skills in a general purpose high-level programming language used for Internet-based data collection and analysis. I strongly recommend the Python programming language although other programming languages like Ruby and Perl are also good choices. Generally speaking, statistical programming languages like R, Stata, Matlab are not well suited for this.
2. Familiarity with the technologies of web APIs. In particular, students should understand what APIs are, how they work, and should be able to read, interpret, and process data in JSON.
3. Knowledge of how to process and and move data from a website or API into a format that they will be able to use for analysis. The final format will depend on the nature of the result but this might be a statistical programming environment like R, Stata, SAS, SPSS, etc or a qualitative data analysis tools like ATLAS.ti, NVivo or Dedoose.

If you are already comfortable doing these things, great.

If you are not yet comfortable, I am going to be organizing three free workshops called the Community Data Science Workshops on Saturdays in April and May and I extremely strongly recommend that you attend them. The workshops will teach exactly the skills I'm expecting you to have and attending the workshops will be enough to fulfill this requirement.

The workshops will meet four times so please block these out on your calendar now:

1. Friday 4/8 6-9pm
2. Saturday 4/9 9:45am-4pm
3. Saturday 4/23 9:45am-4pm
4. Saturday 5/7 9:45am-4pm

I have taught these workshops twice before in the Spring and Fall quarters of 2014 and 2015. If you have taken them in the past, you do not need to take them again. If you are feeling unsure about your skills, you will be welcome to come back to review and brush up on the material.

If you do not have the technical skills required above and you will not attend the workshops, you're going to be responsible for learning this material on your own. If you know you will be in this situation, contact me before the quarter starts.