Module Details

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title Big Data and Society: Foundations, Politics, and Policy A
Code COMM751
Coordinator Dr TE Nicholls
Communication and Media
T.E.Nicholls@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2021-22 Level 7 FHEQ First Semester 30

Aims

This module aims to introduce students to the study of online media and platforms, with a particular focus on ‘big’ social trace data. As well as developing their understanding of how Internet-based media systems work, students will learn about the strengths and weaknesses of using big data for social science research, and engage with key online political communication policy questions.


Learning Outcomes

(LO1) Students will analyse interactions between the media, platforms, and citizens.

(LO2) Students will develop their understanding of how digital data is generated, collected and used in the modern world.

(LO3) Students will engage with key current debates around media, data and society.

(LO4) Students will develop a proposal for their thesis.

(S1) Students will develop their skills in building and presenting an argument, while selecting appropriate sources.

(S2) Students will be able to link key public policy questions to social science research approaches that could help practically address them.

(S3) Students will develop skills in critically engaging with evidence.

(S4) Students will further develop their academic writing skills.


Syllabus

 

The content of the module is research-driven and contemporary. Students will attend an overview lecture, and will then be asked to complete independent reading in preparation for an active seminar. Seminars will start with a presentation by a member of the class on the assigned readings, and will then continue with a guided class discussion. A key text for the course is Matthew Salganik’s Bit By Bit. This text is available in print, but also as a freely-available online book.

The content for this module is broadly divided into two blocs. The first bloc covers foundations, with content such as the development of the Internet and social media, the characteristics of big data (both helpful and unhelpful), issues with access to data and platform gatekeeping, social science methods for using data, the nature of social networks, and understandings of social media and user content. The second bloc goes into more depth into some of the opportunities and threats that arise in on line political communication, covering topics such as misinformation, disinformation and trolling; hate speech and radicalisation; participation, protest, polarisation, and echo chambers; and the effects of digital and social media on well-being.


Teaching and Learning Strategies

Summary of Learning and Teaching Methods:
Teaching method: Lectures and seminars
Description: Weekly lecture plus weekly seminar
This activity may be online or on campus and could be subject to changes.
Schedule directed student hours: 24
Unscheduled directed student hours: 276

Attendance recorded: YES
Notes: Lecture ideally before seminars
Description of how self-directed learning hours may be used: Reading key and suggested literature, reviewing lecture slides, researching and writing the formative coursework, developing the student’s dissertation proposal, researching and writing the summative coursework.


Teaching Schedule

  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 12

12

      276

300
Timetable (if known) 60 mins X 1 totaling 12
 
60 mins X 1 totaling 12
 
         
Private Study 0
TOTAL HOURS 300

Assessment

EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
             
CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
Summative essay Resit opportunity - Y Anonymous - Y  words    60       
Dissertation proposal Resit opportunity - Y Anonymous - N  words    40       
Formative essay Resit opportunity - N Anonymous - N  words         

Recommended Texts

Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.