GV2ATANU: Analysing Social Data: Techniques and Applications

Module code: GV2ATANU

Module provider: Geography and Environmental Science; School of Archaeology, Geography and Environmental Science

Credits: 20

Level: Level 2 (Intermediate)

When you'll be taught: Semester 1

Module convenor: Professor Steve Musson, email: s.musson@reading.ac.uk

NUIST module lead: Buda Su, email: subd@nuist.edu.cn

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: No

Talis reading list: Yes

Last updated: 20 May 2024

Overview

Module aims and purpose

This module will explore the analysis of social data, using quantitative and qualitative. We will use social data to persuade, argue and illustrate our understanding. During the module, you will become a better informed, more confident and critical user of social data. 

The first section of the module deals with quantitative (i.e. numerical) approaches. We will develop technical analysis skills using Excel and put these into practice with a large dataset such as the  census data. The emphasis will be on applying simple analytical techniques to secondary data sources and no great level of mathematical ability is assumed.

The second section of the module deals with qualitative approaches. We will develop a different set of analytical techniques and better understand how we can interpret textual documents. The emphasis will again be on using secondary data and we will put these techniques into practice using a large dataset such as the Mass Observation Archive. If possible, we will visit a public record archive to better understand these data sources.

Students have often found these techniques useful in dissertations, other research projects, and in future employment. As such, this module can be the gateway for further research and professional development.

The module aims to:

1. To encourage students to understand social data as a socio-political product and to enable them to reflect on the epistemological and methodological implications of this perspective;
2. To empower students to become critical users of social data, with particular reference to the relative strengths and weaknesses of a range of data sources;
3. To develop students' confidence in finding and using social data for research purposes, including the development of a range of analytical and visualisation techniques that allow them to understand the possibilities of different types of social data. 
4. To enable students to develop data analysis techniques relevant to a wide range of sources.
5. To apply these skills to a range of qualitative and quantitative data sources to answer research questions.

Module learning outcomes

By the end of the module, it is expected that students will be able to:

1. Identify different sources of social data and think critically about their potential utility  
2. Demonstrate their ability to manipulate social data, conduct appropriate analysis and display their results in an appropriate way  
3. Use social data to make a compelling and evidenced argument   
4. Reflect on their use of social data in a way that demonstrates a critical understanding of socio-political processes of data production

Module content

This module begins with seminars that introduce students to key features of social data, research applications and critical interpretation of its role in the creation of knowledge. Students will encounter, manipulate and analyse a range of social data. This will initially take the form of teaching data sets, but students will later be expected to obtain their own data in an informed and critical manner. Towards the end of Semester 1, students will work on a small data analysis task, in which they will be expected to demonstrate their ability as a critical user of social data. In Semester 2, students will be introduced to qualitative social data, including some of the main analytical techniques used to understand and interpret such sources. We will use a series of practical exercises to explore the philosophy and practice of qualitative research and develop a tool kit students can use in their independent research.

Structure

Teaching and learning methods

This module will be delivered through a mixture of lectures and practical classes. A companion website will support learning with supplementary material including sample datasets and worked through exercises. The emphasis will be on student-led discussion and problem solving, rather than direct instruction.

Study hours

At least 40 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 40% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: https://www.reading.ac.uk/cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

Reassessment

Additional costs