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 | DOING TWITTER ANALYTICS | ||
Code | SOCI573 | ||
Coordinator |
Dr PD Brooker Sociology, Social Policy and Criminology P.D.Brooker@liverpool.ac.uk |
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Year | CATS Level | Semester | CATS Value |
Session 2020-21 | Level 7 FHEQ | Second Semester | 5 |
Aims |
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To introduce students to key methodological concerns of working with Twitter data. To guide students in gaining first-hand experience collecting, visualising and exploring Twitter data. To enable students to see how to make sense of Twitter data for social scientific purposes. To point towards a more general role for social media and digital data in social science research. |
Learning Outcomes |
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(LO1) Understand the methodological continuities and discontinuities between social media analytics and 'traditional' social science methods. |
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(LO2) Be able to extract and visualise Twitter data using research-oriented software. |
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(LO3) Be able to reflect on the methodological link between the technical aspects of Twitter analyticsresearch work and the social scientific findings that result. |
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(LO4) Appreciate the potential for social media and digital data analytics to provide insight on social scientific research topics. |
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(S1) Digital researching; participating in emerging academic practices that both leverage and concentrate topically on digital social interaction |
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(S2) The application of software and information technology in developing, addressing and presenting scholarly research |
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(S3) Research management skills, including elements such as developing and piloting a research strategy, engaging in considerations of ethics in regard to (digital) research data, undertaking exploratory empirical research involving data collection, visualising and making sense of data, and presenting research in written format |
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(S4) Problem solving and creative critical thinking; making sociogical sense of data which is not produced (primarily) for the purposes of social scientific research |
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(S5) Reflexive thinking around the research process; self-analysis of the journey from software tools and "raw" data to social scientific explanations of it |
Syllabus |
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The teaching and learning strategy of the module is based around providing students with the knowledge and skills necessary to engage with Twitter data, practically and methodologically, from the social scientific perspective. Having received guidance from the module leader in the workshop sessions, students will be able to explore these ideas for themselves through an independently-conducted small-scall research project. Teaching will take place over two days. Day 1 will comprise a one hour lecture, a one hour tutorial, and a two hour lab practical session. Day 2 will comprise a four hour lab practical session. |
Teaching and Learning Strategies |
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Teaching Method 1 - Lecture Teaching Method 2 - Tutorial Teaching Method 3 - laboratory Work |
Teaching Schedule |
Lectures | Seminars | Tutorials | Lab Practicals | Fieldwork Placement | Other | TOTAL | |
Study Hours |
8 |
8 | |||||
Timetable (if known) |
240 mins X 1 totaling 8
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Private Study | 42 | ||||||
TOTAL HOURS | 50 |
Assessment |
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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 |
Research Report There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When) :Semester 2 | 2000 Words | 100 |
Recommended Texts |
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Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module. |