Join us for 3 class sessions and two one-on-one meetings with our instructors.
This intensive week long event connects students, scholars and analysts with the NodeXL Team to learn to collect, analyze, visualize, report and present insights into collections of connections, like social media.
Day 1: July 27 – Introduction to networks, social networks, and social media networks!
Day 2: July 29 – Intermediate network analysis – automation, YouTube, Wikis, and more!
Day 3 : August 3 – Student project and discussion
If you can make a pie chart, you can now make a network chart!
Gain insights into collections of annotated connections.
Discover the key people leading each topic discussed in social media. Identify groups, factions, divisions and market segments in a discussion stream.
All students receive a free trial NodeXL Pro desktop user license for 60 days past the day of the class.
Learn to “Think Link” and gain insights into collections of connections found in social media and beyond!
About this Event
This event will introduce the importance of social media research & provide an overview of NodeXL Pro for the analysis of social media data.
*This event is capped with only a limited amount of discounted academic and student tickets…act to secure your ticket*
NodeXL provides easy access to social media network data streams, advanced network metrics, text and sentiment analysis, and powerful report generation with just a few clicks.
This session will be led by Dr. Marc Smith from the Social Media Research Foundation with guest speakers who will demonstrate network methods for research insights.
The event will be delivered online via Zoom. You will receive a meeting link 7-days before the workshop. The event will be recorded.
Organized by the Social Media Research Foundation.
Learn tips and tricks for downloading and social media data for your project!
No previous knowledge required.
By attending, you’ll gain a digital certificate and a 2 month trial access to NodeXL.
The need to gain insights into social media has grown in importance with the increasing popularity of social networking websites in particular (e.g. Twitter, YouTube, Facebook, LinkedIn, and Instagram etc.) and social computing in general. As people increasingly participate in online communities for social, commercial, and civic interaction, new methods are needed to study these phenomena.
The event will focus on providing an overview of NodeXL and Social Network Analysis and will guide delegates on all the steps required to be able to use the tool to download and analyze social media data.
On completion, delegates will be emailed a certificate of attendance (PDF) and the skills that have been gained.
• Learn the required theories and concepts of networks and social networks
• Learn how to prepare your data for network analysis
• Learn the basics of the NodeXL Pro application
• Learn how to do automated analysis in NodeXL Pro
• Learn to identify key people and groups on social networks
• Learn how to run content analysis to create a vector of words, hashtags and URLs for each users, group, and population
• To understand how to interpret the network metrics
• To install and run NodeXL Pro
• To know the best practices on customizing network analysis to adapt to different data sources
• To learn how to build a network based strategy in your own organization
Who will benefit from this course?
This event will benefit a wide range of people including, but not limited to:
* Academics/ Researchers
* Masters and PhD students
* Research Support Staff and Managers
* Library and Information Professional
* Communications and Marketing Professionals
* Finance/Banking Professionals
• Installing NodeXL Pro
• Data preparation and cleaning methods – “think link”!
• Data about relationships, entities, and groups
• Content analysis
• Introduction to network structures: power laws, preferential attachment and the 1-9-90 law
• Identification of influential contributors (thought leaders)
• Network centrality and clustering algorithms
• Data visualization: drawing collections of connections
• Descriptive Statistics for Networks
• Exploratory analysis of networks
• Reporting and presenting network insights