• Class Number 6361
  • Term Code 3260
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Dr Robert Ackland
    • Dr Robert Ackland
  • Class Dates
  • Class Start Date 25/07/2022
  • Class End Date 28/10/2022
  • Census Date 31/08/2022
  • Last Date to Enrol 01/08/2022
SELT Survey Results

The Internet is increasingly a source of data for social science research and this course provides students with training in online research methods for social research, with an emphasis on quantitative methods. The course focuses on unobtrusive/non-reactive methods involving socially-generated digital trace data (networks and text) from sources such as websites, social networking sites such as Facebook, microblogs such as Twitter and discussion environments such as Reddit. In this computer-lab based course, students will gain an introduction to coding and will undertake social network analysis and quantitative text analysis using the R statistical software. There is also an overview of obtrusive/reactive social research methods, including both quantitative methods (online surveys, online experiments) and qualitative methods (online focus groups and interviews, online field research).

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. compare online research methods to methods traditionally used by social scientists;
  2. undertake basic coding using the R statistical software;
  3. collect digital trace data and conduct basic social network and text analysis;
  4. locate available tools and data for online research; and
  5. understand the advantages and disadvantages of various online research methods, and their ethical implications.

Required Resources

In 2022 (for the first time since this course started), the computer lab classes will not be run using ANU Information Commons (IC) computers (either physical or virtual). We will use the computer lab space for the hybrid computer lab classes, but the instructor and students will be required to use their own laptops or PCs in order to undertake the lab class activity and any associated assessment. Prof Ackland will explain the reason for this in the first class. So, to participate in this course you need to have your own laptop (if you are attending the hybrid computer labs on campus) or PC otherwise, and install: R/RStudio, additional R packages, and Gephi for network visualisation. These are free and open source software. Instructions for installation will be provided on the wattle site.

Staff Feedback

Students will be given feedback in the following forms in this course:

  • written comments
  • verbal comments
  • feedback to whole class, groups, individuals, focus group etc

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

Class Schedule

Week/Session Summary of Activities Assessment
1 Lecture: Introduction to course; Online research methods, digital trace data, and networks Lab: Introduction to R and RStudio, Introduction to SNA using VOSONDash
2 Lecture: Social network analysis - 1: What is a social network, types of networks Lab: Introduction to SNA using R/igraph, Collecting Twitter data using VOSONDash
3 Lecture: Social network analysis - 2: Basic SNA metrics; Microblogs Lab: Twitter network analysis; Collecting Reddit data
4 Lecture: Social network analysis – 3: Clustering and homophily in networks; Threaded conversation networks Lab: Reddit network analysis; Collecting YouTube data A1 due 15 August
5 Lecture: Content analysis - 1: Discourse & word frequencies Lab: Analysing clustering and homophily; Network visualisation using Gephi
6 Lecture: Content analysis - 2: Discourse & frame analysis/topic modelling Lab: Word frequencies, word clouds, comparison clouds
7 Lecture: Content analysis - 3: Sentiment Lab: Frame analysis and topic modelling A2 due 19 September
8 Lecture: Content analysis – 4: Analysing content using network analysis Lab: Sentiment analysis
9 Lecture: Platforms – 1: Platform architecture and affordance Lab: Co-occurrence analysis, Semantic network analysis
10 Lecture: Platforms – 2: Bots and inauthentic coordinated behaviour Lab: Collecting Twitter conversation network data
11 Lecture: Content analysis – 5: Memetics Lab: Identifying bots and inauthentic coordinated behaviour A3 due 17 October
12 Lecture: Virtual Worlds, Web experiments; Online surveys Lab: Identifying and analysing memes; Collecting WWW hyperlink network data
13 Examination period A4 due 7 November

Tutorial Registration

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

Assessment Summary

Assessment task Value Due Date
Basic social network analysis 15 % 15/08/2022
Social media network collection and analysis 35 % 19/09/2022
Content analysis 15 % 17/10/2022
Combining methods 35 % 07/11/2022

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details


ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Integrity . In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Assessment Task 1

Value: 15 %
Due Date: 15/08/2022
Learning Outcomes: 

Basic social network analysis

word limit: 900 words

Assessment Task 2

Value: 35 %
Due Date: 19/09/2022
Learning Outcomes: 

Social media network collection and analysis

word limit: 2100 words

Assessment Task 3

Value: 15 %
Due Date: 17/10/2022
Learning Outcomes: 

Content analysis

word limit: 900 words

Assessment Task 4

Value: 35 %
Due Date: 07/11/2022
Learning Outcomes: 

Combining methods

word limit: 2100 words

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. At its heart, academic integrity is about behaving ethically, committing to honest and responsible scholarly practice and upholding these values with respect and fairness.

The ANU commits to assisting all members of our community to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to be familiar with the academic integrity principle and Academic Misconduct Rule, uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with.

The Academic Misconduct Rule is in place to promote academic integrity and manage academic misconduct. Very minor breaches of the academic integrity principle may result in a reduction of marks of up to 10% of the total marks available for the assessment. The ANU offers a number of online and in person services to assist students with their assignments, examinations, and other learning activities. Visit the Academic Skills website for more information about academic integrity, your responsibilities and for assistance with your assignments, writing skills and study.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Late submission permitted. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

Returning Assignments

Via Wattle Turnitin submission.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

Students are not able to resubmit assignments once they have been marked, but Turnitin similarity checking will be available prior to final submission.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Dr Robert Ackland
6125 0312

Research Interests

Dr Robert Ackland

By Appointment
Dr Robert Ackland
6125 0312

Research Interests

Dr Robert Ackland

By Appointment

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions