REU Ad - 2015-01-22

National Science Foundation Research Experience for Undergraduates (REU)
“Constructing and Validating an Automated Coding System for Protest Events in Electronic News Sources.”
Principal Investigators: Pamela Oliver, Professor, oliver@ssc.wisc.edu, Chaeyoon Lim, Associate Professor,
clim@ssc.wisc.edu, Alex Hanna (grad student).

This opportunity is for undergraduates interested in social science or media studies to provide research assistance
on a part-time basis during the spring 2015 semester. Depending on schedules and the flow of work, there may be opportunities to
continue during the summer. REU participants will be paid a stipend of $100 a week with an expectation of 10
hours a week of research assistance, meeting attendance, and background reading. Depending on student needs
and interest, we will consider students who wish to work 5-15 hours a week on the project, with proportional
adjustment in the stipend.

The goal of this project is to use machine learning approaches to develop an automated system for identifying and
coding protest events in news sources. Part of this project involves having human coders search for and code news
articles about protest to use as training sets for the machine learning process. Undergraduate research assistants
will work on computers to 1) search for and retrieve news stories from library or Internet sources, 2) read news
stories and mark the portions of them that refer to protests, and 3) read news stories and code features of
protests, such as their size or location. This work can be done in campus computer labs or on the student’s own
computer with Internet connection. Students will learn techniques for coding and content analysis of news media
as well as gaining familiarity with applications of new data science and big data for social science problems.
Students will also be introduced to important research issues such as sampling, assessing measurement validity
and reliability, and the processes of large collaborative research projects.

Expectations: REU participants will be expected to: (1) Complete assigned background reading about the
sociological and methodological issues in identifying protests in news sources and issues in machine learning. (2)
Attend weekly team meetings that will focus both on practical aspects of the project and general principles of
scientific inquiry and possible professional paths in social science. (3) Keep a work log and to stay current with their
time commitments to the project

Qualifications: This project requires the ability to read news articles in English fairly rapidly and with good
understanding of idiomatic English writing. You will have to be able to read the texts and decide how to classify
them into sociological categories. Accuracy and attention to detail are essential. You should have a track record of
reliability and quality work in classes or jobs. We prefer sociology or other social science or media studies majors
and prefer students who have taken a basic research methods class. Students who are from disadvantaged or
historically underrepresented groups are especially encouraged to apply.

To apply: Send an email to Pamela Oliver (oliver@ssc.wisc.edu) with the following information: (1) A statement of
(a) why this position interests you, (b) what your academic/career goals are, (c) how this position fits into your
academic and career goals, (d) your relevant skills and background. The suggested length for this statement is a
couple of paragraphs, one page at most. (2) An unofficial transcript printed out from my.wisc.edu that shows your
names and the courses you have taken and grades received. (3) The names & contact information (email address
and telephone number) of references. Ideally you will have at least one reference who can attest to you reliability
as a worker and one who can attest to your academic ability.

Note: We are also recruiting participants to participate for course credit in Sociology 320, Research Practicum. You
can either get course credit or be paid, but not both. If you are interested in both possibilities, you can submit one
application for both, stating your preference between the paid REU and course credit. Course credit participants will
earn 3 credits for a 10 hours/week commitment and 2 credits for a 7 hours/week commitment.