Description:

This course introduces participants to approaches for collecting and analysing network and text data from social media, (Reddit, YouTube and Mastodon) and the WWW (hyperlink networks).

In terms of analysis, the focus is on the application of social network analysis (SNA) and quantitative text analysis to online data.

While the main software used in the course is R, we also introduce Gephi for advanced visualisation. Data collection is via the VOSON R Packages (VOSON Dashboard, vosonSML). We also cover other important R packages for network and text analysis such as: igraph (network analysis and visualisation), quanteda (quantitative analysis of textual data), tidytext (text mining), and wordcloud (text word clouds).

The course will be particularly useful to academics and PhD students who want to become more computationally literate, and those from technical disciplines (e.g. computer science, engineering, information science) who want to become more familiar with social science approaches to analysing social media data. The course will also be useful for people from industry and government whose work involves quantitative analysis of social media data, e.g. for marketing, social research, public relations, brand management, journalism, opinion analysis.

Start: Monday, 10 February 2025 @ 16:30

End: Thursday, 13 February 2025 @ 21:30

Duration: 3 afternoon/ evenings

Timezone: Melbourne

Venue: Online

 Country: Australia

Prerequisites:

It is advisable that you have taken the following ACSPRI course, or have had some equivalent exposure to social network analysis (see ACSPRI website for details):

*Introduction to Social Network Research and Analysis

It is also advisable that you have some experience with the R programming language (or similar languages) for example, via the following ACSPRI courses:

*Data Analysis in R
*Introduction to R
*Advanced Statistical Analysis in R
Learning Objectives:

This course introduces participants to approaches for collecting and analysing network and text data from Social Media, (Reddit, YouTube and Mastodon) and the WWW (hyperlink networks) using the R statistical software.

Eligibility:
  • Open to all

Organiser: ACSPRI

Contact: info@acspri.org.au

Host institution: ACSPRI

Keywords: social network research, Social network analysis, social media data, R statistical software, quantitative, Reddit, YouTube, Mastodon

Fields: INFORMATION AND COMPUTING SCIENCES, ENGINEERING, TECHNOLOGY, MEDICAL AND HEALTH SCIENCES, EDUCATION, COMMERCE, MANAGEMENT, TOURISM AND SERVICES, STUDIES IN HUMAN SOCIETY, PSYCHOLOGY AND COGNITIVE SCIENCES

Capacity: 12

Event type:
  • Workshop
Tech Requirements:

This course will be run online, via Zoom.

To ensure that participants are well prepared for the course, there will be detailed instructions for installing the required software: R, RStudio, required R packages and Gephi. There will also be preliminary exercises (introduction to R and RStudio) that the participants will be expected to complete before the course. The instructor will be available for consultation (via email or Zoom) prior to the course, to provide assistance with installation of software and the preliminary exercises.

Cost Basis: Cost incurred by all

Social Media Network and Text Analysis: Online https://dresa.org.au/events/social-media-network-and-text-analysis-online-f6093406-3c70-4ce9-b6bc-95bcc4a4898d This course introduces participants to approaches for collecting and analysing network and text data from social media, (Reddit, YouTube and Mastodon) and the WWW (hyperlink networks). In terms of analysis, the focus is on the application of social network analysis (SNA) and quantitative text analysis to online data. While the main software used in the course is R, we also introduce Gephi for advanced visualisation. Data collection is via the VOSON R Packages (VOSON Dashboard, vosonSML). We also cover other important R packages for network and text analysis such as: igraph (network analysis and visualisation), quanteda (quantitative analysis of textual data), tidytext (text mining), and wordcloud (text word clouds). The course will be particularly useful to academics and PhD students who want to become more computationally literate, and those from technical disciplines (e.g. computer science, engineering, information science) who want to become more familiar with social science approaches to analysing social media data. The course will also be useful for people from industry and government whose work involves quantitative analysis of social media data, e.g. for marketing, social research, public relations, brand management, journalism, opinion analysis. 2025-02-10 16:30:00 UTC 2025-02-13 21:30:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all social network researchSocial network analysissocial media dataR statistical softwarequantitativeRedditYouTubeMastodon