Webinar: Web-scraping for Social Science Research: Websites as a Source of Data

Date:

23/04/2020

Organised by:

UK Data Service

Presenter:

Dr Diarmuid Mcdonnell

Level:

Entry (no or almost no prior knowledge)

Contact:

Gillian Meadows
Gillian.Meadows@manchester.ac.uk

video conference logo

Venue: Online

Description:

Vast swathes of our social interactions and personal behaviours are now conducted online and/or captured digitally. In addition to common sources such as social media/network platforms and text corpora, websites and online databases contain rich information of relevance to social science research. Thus, computational methods for collecting data from the web are an increasingly important component of a social scientist’s toolkit.

 

This free webinar, organised by the UK Data Service, is the second in a series of three on how to collect data from the web using computational methods. Specifically, this webinar delineates the value, logic and process of capturing data stored on websites. Presented by Dr Diarmuid McDonnell of the UK Data Service, this webinar will cover the step-by-step process of collecting data from a web page, including providing sample code written in the popular Python programming language. It demonstrates web-scraping techniques for capturing real-time information on the Covid-19 pandemic, as well as for the author’s own research specialism (charitable organisations).

 

Webinar one, on 27 March, will provide an example of a published piece of social research that utilised web-scraping techniques to generate a novel, linked administrative dataset to evaluate a regulatory intervention.

 

Webinar three, on 30 April, will demonstrate how to use application programming interfaces (APIs) to download data from the web, again using the Python programming language.

 

There is also a parallel webinar series focusing on getting, storing and manipulating data that illustrates a variety of complementary techniques for collecting data from the web.

Cost:

Free

Website and registration:

Region:

International

Keywords:

Data Collection, Data Quality and Data Management , Mixed Methods Data Handling and Data Analysis

Related publications and presentations:

Data Collection
Data Quality and Data Management
Mixed Methods Data Handling and Data Analysis

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