Webinar: Introduction to Text-Mining
Date:
02/06/2020
Organised by:
UK Data Service
Presenter:
tbc
Level:
Entry (no or almost no prior knowledge)
Contact:
Christine Dorisamy-Pillai
cdoris@esex.ac.uk
Venue: Online
Description:
Online, 13.00 - 14.00 BST
Text-mining is one of many data-mining techniques that social scientists are using to turn unstructured (or more accurately, semi-unstructured) material into structured material that can be analysed statistically. In this way, researchers are gaining access to new materials and methods that were previously unavailable. As such, it is increasingly important that social scientists have a clear understanding of what text-mining is (and what is isn't) as well as how to use text-mining to achieve some basic and more advanced research outcomes.
This free webinar, organised by the UK Data Service, is the first in a series of three on understanding and using text-mining methods within social science research contexts.
The first webinar covers the concepts behind fully structured and semi-unstructured data, the theory behind capturing and amplifying existing structure, and the four basic steps involved in any text-mining project.
Webinar two will dive into the steps needed to do some of the most common text-mining analyses and will be accompanied by an online interactive notebook that allows participants to see, edit and execute the demonstrated code.
Webinar three then rounds off the series by diving into the concepts behind more advanced text-mining analyses, presenting some sample code that participants may find useful, and introducing some work that provides further learning opportunities. This webinar will also be accompanied by an online interactive notebook that allows participants to see, edit and execute the demonstrated code.
Slides and recordings of UK Data Service webinars are made available on our past events pages and YouTube channel soon after the event has taken place.
Cost:
free
Website and registration:
https://www.ukdataservice.ac.uk/news-and-events/eventsitem/?id=5627
Region:
International
Keywords:
Data Collection
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