Web Scraping and Digital Power (few places remaining)

Description:

Web scraping has great potential as a research tool that can be applied across various fields of research including social science and humanities, and allows us to reach beyond the ‘quantitative and qualitative divide’. The programming and code-reading/analysing skills used in web scraping can enhance our understanding of digital power beyond the traditional limits of computing techniques.

This two-hour training module (plus 1-hour online Q&A session) introduces researchers to how to use Python software for web scraping. You will learn what web scraping means, the principles behind it, and ethical considerations, and importantly how to use Python to achieve web scraping. The module provides a good opportunity to learn how to enhance your coding and code-reading skills, from which you can reflect on how digital power especially web scraping and coding is shaping contemporary research. The training is programming beginner friendly.

For the 1hr online Q&A session the first 30mins are used for extend web scraping with other tools including R, followed by Q&A tutorials. Please ensure you have basic knowledge in using R if you would like to join the first 30mins, but the Q&A are available to all the students.

Cost:

Please contact the admin for details. It might be free for specific external partners.

Website and registration:

Register for this course

Region:

International

Keywords:

Frameworks for Research and Research Designs, Data Collection, Data Quality and Data Management , Qualitative Data Handling and Data Analysis, Quantitative Data Handling and Data Analysis, Mixed Methods Data Handling and Data Analysis, ICT and Software, ATLAS.ti, Python, R, Research Management and Impact, Research Skills, Communication and Dissemination, Web scraping, research ethics, AI + research

Related publications and presentations from our eprints archive:

Frameworks for Research and Research Designs
Data Collection
Data Quality and Data Management
Qualitative Data Handling and Data Analysis
Quantitative Data Handling and Data Analysis
Mixed Methods Data Handling and Data Analysis
ICT and Software
ATLAS.ti
Python
R
Research Management and Impact
Research Skills, Communication and Dissemination

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