SOS2920 ¨C Introduction to Digital Research Methods

Course content

An ever larger part of our time and our social and professional lives takes place on the internet. This goes for our love lifes, for our interaction with friends and acquaintances, for our participation in democratic and public debate - or in almost any other debate; it goes for our relation to the politicians we elect, our use of news media and our search for knowledge and information; just as it goes for our interests in fashion or cultural trends or virtually any other cultivation of interests, hobbies or political opinions.

Due to this increasing digitalization of social life, these communicative exchanges and interaction patterns are often retrievable and open to analysis with digital means. This opens up new social scientific and empirical possibilities, which a new field of digital methods seeks to exploit. This new field of digital methods - possessing its own degree of strengths and weaknesses - has begun to take shape between traditional quantitative and qualitative conceptions of method.

This course provides a basic introduction to the field of digital methods for undergraduate students. It requires no coding or programming skills or prior experience with digital research tools. It centers on hands-on exercises and mini-projects to explore the potential utility and versatility of a broad range of tools (e.g., for issue crawling and ¡®mapping¡¯, data scraping, text mining and visualizing data). The course teaches students to extract or ¡®scrape¡¯ text and interaction data from the Internet, including important social media platforms, and to visualise and analyse these data in novel ways and with novel means. The course will considerably augment the student¡¯s range of means to access and analyse empirical material more generally: it is meant to generate competences which can be of use to complement and nuance virtually any social scientific investigation (in tandem (or not) with traditional methods). The course also touches upon more theoretical aspects and discussions associated with digital sociology and the use of digital methods, including theories about how (social) media frames and informs interaction, about the relationship between the digital and the social, and about the ethical implications and problems of digital research. Yet, it focuses on the development of technical skills and upon gaining familiarity with the software tools introduced during the course.

Enrolled students should prepare for unavoidable frustrations with the software tools used in the course. The fast-changing reality of the Internet and the changing strategies of major web service providers such as Google and social media platforms like Facebook towards external researchers creates a number of difficulties.

IMPORTANT! All students need to commit to working in groups of 3-5 during the semester. If you are not prepared to engage in group work, this course is not for you. These groups will be formed by the instructors during the first month of the course, and barring exceptional circumstances, they will remain stable throughout the course. Importantly, students will take their final exam in these groups (see below).

Learning outcome

Learning Objectives

At the end of the course, students will

• Have experience with (freely accessible) software tools permitting extraction and analysis of interaction data and text from internet sites and important social media platforms
• Have knowledge about the distinct nature of digital research methods and how they differ from and may complement conventional methods (qualitative and quantitative)
• Be capable of reflecting on the ethical challenges associated with digital methods and develop responsible research strategies
• Have insight into the main theories as to how digital media and their designs perform social action and affect social experience online as well as more broadly
• Have gained acquaintance with the main themes of digital sociology and digital social science more generally

Admission to the course

Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.

If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures.

Teaching

Number of lectures

The course entails 11 two-hour lectures and one workshop for student exam project development (without preparation).

Obligatory Coursework

There are two types of obligatory coursework, both need to be passed before taking the exam.

1. Each student has to complete one small individual homework assignment in week 4 of the course. The assignment is graded pass/fail. A pass is required to be admitted to the final exam. The assignment can be retaken if the student does not pass the first attempt.

2. All students are required to attend the term paper preparation workshop, contribute to the collective development of an exam project, and participate in the group¡¯s work when carrying out the actual project.

In addition to the obligatory assignment, we will offer a number of voluntary small homework assignments, which are tied to specific lectures and support students¡¯ learning, especially the use of the software tools. These will be group assignments, i.e., they have to be completed by a group of students. All assignments are graded pass/fail. Students will engage in peer-assessments for some of these assignments - grading the work of other students in the class

Software Installations

All students will have to install the following software tools on their personal laptops. We will provide installation support during the first week of the course.

• Hyphe: - https://github.com/medialab/hyphe

• Gephi: https://gephi.org/users/install/

• Facepager (Install the 4.3.10 version): https://github.com/strohne/Facepager

• Excel or other spreadsheet program

Examination

Term paper

The final evaluation will consist of a group project and term paper. To the extent possible, students will complete the term paper in the same groups they have worked in throughout the course. Group adjustments might be required, e.g., due to withdrawals or illness. Group compositions for the term paper will be posted on Canvas one week before the term paper writing period starts.

• Guidelines for the group exam in SOS2920

• Previous exams and assessment guidelines

Project Description:?Each group will collectively develop their term paper project (description) during the preparation workshop at the end of the semester. Note that participation (physical presence) in the workshop is mandatory. Each group will write a synopsis about their project (max 200 words) during the workshop. The synopsis of the group project must be approved by the instructors. The proposed project must meet the following criteria:

• Apply at least one of the tools introduced in one of the lectures for data extraction from at least one Internet platform (e.g., Wikipedia, Twitter, Facebook) and/or traditional websites,
• Include the use of network visualisation software (e.g., Gephi),
• Use at least one of the text mining devices introduced during the course (e.g., Voyant Tools).
• Discuss at least one theoretical and one ethical issue related to the project.

Students will complete their previously approved project and collaboratively draft a group paper (maximum 4000 words in a five-person group,+/¡Â 500 words pr. person; the final word limit will depend on group size). In addition, each group will fill out a group work form (available on Inspera), answering questions about their collaborative process. The form has to be attached to the collaborative paper; both documents have to be submitted as a single pdf file. Each exam should have a cover page that lists the exam ID of all group members.

Logistics: While each group writes a collective paper, each individual student has to submit their group¡¯s paper in Inspera by the exam deadline. In other words, multiple students will submit the same exam document. The document must contain three components: (1) cover sheet with all group member exam IDs, (2) collaborative paper, (3) group work form.

Grading: UiO letter grading policies (A-F) apply. All members of a group will receive the same grade. Please note that individual appeals and complaints can result in a different grade for the appealing/complaining student - but that this change of grade (given to the appealing student) will not affect the grade of the other group members.

Language of examination

The examination text is given in English, and you submit your response in English.

Grading scale

Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.

More about examinations at UiO

• Use of sources and citations
• Special exam arrangements due to individual needs
• Withdrawal from an exam
• Illness at exams / postponed exams
• Explanation of grades and appeals
• Resitting an exam
• Cheating/attempted cheating

You will find further guides and resources at the web page on examinations at UiO.