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*****  To join INSNA, visit http://www.insna.org  *****

Dear SOCNET list,

Please consider signing up for the following workshop at the upcoming 
2016 Sunbelt conference, Newport Beach, California 
(http://insna.org/sunbelt2016/).

Workshop registrations close 7th March.

---------------------------
Collecting and Analyzing Social Media Data Using SocialMediaLab
Session Time: Tuesday April 5 th , 8:00am – 11:00am
Workshop Length: 1 session (3 hours)
Attendance Limit: 30
Instructors:  Robert Ackland (Australian National University), 
[log in to unmask]
Timothy Graham (University of Queensland), [log in to unmask]

VOSON SocialMediaLab is an R package that provides a suite of tools for 
collecting and constructing networks from social media data. It provides 
easy-to-use functions for collecting data across popular platforms 
(Instagram, Facebook, Twitter, and YouTube) and generating different 
types of networks for analysis. SocialMediaLab also collects the 
associated text data from social media platforms (e.g. Tweets, Facebook 
fan page posts and comments, YouTube video comments).

In this workshop, participants will learn how to collect various types 
of social media data using SocialMediaLab and generate different types 
of ‘ready-made’ networks for analysis. Participants will also learn 
basic network and text analysis using R packages such as igraph and tm.

Examples of the networks that can be constructed using SocialMediaLab:
- Instagram: Bimodal network (Instagram users and Instagram posts), with 
edges representing user i ’commenting’ or ’liking’ post j.

- Facebook: Bimodal dynamic network (Facebook users and Facebook posts), 
with edges representing the time(s) when user i commented on post j.
- Twitter: Unimodal network of Twitter users who have tweeted using 
particular hashtag, with edges representing user i mentioned or replied 
to user j in a tweet. Unimodal network of Twitter terms (words and 
hashtags) where edges represent terms i and j co-occurred in at least 
one tweet.
YouTube: Unimodal network of YouTube users who have interacted with one 
another in the comment section for a video (i.e. user i has replied to 
user j or mentioned user j in a comment).

Assumed knowledge: A basic familiarity of R (or other programming 
languages) and basic concepts from network and text analysis.

More info: http://voson.anu.edu.au/SocialMediaLab

-- 

Dr Robert Ackland
Associate Professor, School of Sociology and ANU Centre for Social 
Research and Methods
Leader, Virtual Observatory for the Study of Online Networks (VOSON) Lab 
<http://voson.anu.edu.au>
Australian National University


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