- Class Number 6629
- Term Code 3160
- Class Info
- Unit Value 6 units
- Mode of Delivery In Person
- Dr Robert Ackland
- Prof Adrian Mackenzie
- Class Dates
- Class Start Date 26/07/2021
- Class End Date 29/10/2021
- Census Date 14/09/2021
- Last Date to Enrol 02/08/2021
The Internet is increasingly a source of data for social science research and this course provides students with training in quantitative and qualitative online research methods for social research. The course covers unobtrusive/non-reactive methods involving socially-generated digital trace data (networks and text) from sources such as websites, social networking sites such as Facebook and microblogs such as Twitter. Obtrusive/reactive social research methods are also covered, including both quantitative methods (online surveys, online experiments) and qualitative methods (online focus groups and interviews, online field research).
Upon successful completion, students will have the knowledge and skills to:
- compare online research methods to methods traditionally used by social scientists;
- locate available tools and data for online research;
- collect digital trace data and conduct basic social network and text analysis;
- conduct qualitative online research; and
- understand the advantages and disadvantages of various online research methods, and their ethical implications.
Computer labs will be held either in-person in an ANU Information Commons (IC) computer lab or via zoom. For participating in computer labs, students have three options in terms of how they access the required software (these options depend on the modality of the computer labs i.e. in-person or via zoom):
- Use a computer in the ANU IC computer lab.
- Use own laptop/personal computer, and install R/RStudio, additional R packages, and Gephi. These are free and open source software. Instructions provided on the wattle site.
- Use own laptop/personal computer and install the ANU Virtual Information Commons Remote Desktop.
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
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.
|Week/Session||Summary of Activities||Assessment|
|1||Lecture: Introduction to course (Mackenzie, Ackland); Networks and digital trace data (Ackland) Lab: Introduction to R and RStudio (Ackland)|
|2||Lecture: Social network analysis (Ackland) Lab: SNA using VOSON Dashboard (Ackland)|
|3||Lecture: Online surveys (Ackland) Lab: Collecting Twitter and Reddit network/text data using VOSON Dashboard (Ackland)|
|4||Lecture: Social network analysis (cont.) (Ackland) Lab: Collecting YouTube network/text data using VOSON Dashboard; SNA using R/igraph (Ackland)||A1 due 16 August|
|5||Lecture: Clustering and homophily in online networks; Virtual Worlds (Ackland) Lab: Collecting WWW hyperlink network data using vosonSML; Introduction to network visualisation using Gephi (Ackland)|
|6||Lecture: Web experiments (Ackland) Lab: Studying network clustering and homophily using R/igraph (Ackland)|
|7||Lecture: content analysis I: discourse (Mackenzie) Lab: introduction to scraping & text analysis; platform privacy agreements and R rvest & quanteda (Mackenzie)||A2 due 20 September|
|8||Lecture: content analysis 2: sentiment (Mackenzie) Lab: introduction to sentiment analysis on reddit dataset using quanteda and plots (Mackenzie)|
|9||Lecture: digital ethnography 1: history (Mackenzie) Lab: internet archive and blogosphere (Mackenzie)|
|10||Lecture: digital ethnography 2: controversies (Mackenzie) Lab: wikipedia edits and wikipedia bots (Mackenzie)|
|11||Lecture: social analytics I: apps, sources and platforms (Mackenzie) Lab: mapping platform ecosystems (Mackenzie)||A3 due 18 October|
|12||Lecture: social analytics 2: algorithmic awareness (Mackenzie) Lab: research project design (Mackenzie)|
|13||Examination period||A4 due 8 November|
Please register for computer labs via the wattle site.
|Assessment task||Value||Due Date|
|Basic social network analysis||15 %||16/08/2021|
|Social media network collection and analysis||35 %||20/09/2021|
|Content analysis||15 %||18/10/2021|
|Combining methods||35 %||08/11/2021|
* 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:
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
Basic social network analysis
word limit: 900 words
Assessment Task 2
Social media network collection and analysis
word limit: 2100 words
Assessment Task 3
word limit: 900 words
Assessment Task 4
word limit: 2100 words
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.
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.
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 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.
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.
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.
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).
- ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
- ANU Diversity and inclusion for students with a disability or ongoing or chronic illness
- ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
- ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents undergraduate and ANU College students
- PARSA supports and represents postgraduate and research students