ABSTRACT. This interactive workshop brings early career scholars together to address unique issues they face, develop strategies to achieve career goals, and foster a professional network of social media scholars. We define “early career scholars” as people who have completed the requirements for their terminal degree, but have not advanced to the next level in their field (i.e. post-docs, non-tenured faculty, junior industry researchers). 

We will also have a panel of established scholars to share their insight and experiences:

• David Gauntlett
• Tarleton Gillespie
• Dhiraj Murthy
• Anabel Quan-Haase
• Valerie Steeves

The workshop provides an opportunity to foster community among emerging scholars and to create bridges between junior and senior scholars.

ABSTRACT. An introduction and practical workshop for Social Network Analysis (SNA) and netnography. Please note that previous experience of the topic is not required.

Networks are a data structure commonly found in any social media service that allows populations to author collections of connections. The Social Media Research Foundation's NodeXL project makes analysis of social media networks accessible to most users of the Excel spreadsheet application. With NodeXL, network charts become as easy to create as pie charts. Recent research created by applying the tool to a range of social media networks has already revealed the variations in network structures present in online social spaces. A review of the tool and images of Twitter, flickr, YouTube, Facebook and email networks will be presented. The workshop provides an overview of SNA via NodeXL and demonstrates through theory and practical case studies its application to research, particularly on social media and digital interaction and behaviour records. We also consider the ways in which SNA can be blended with other social media analysis methods such as netnography to create powerful insights from quantitative and qualitative data sets. The workshop will be interactive and there will be opportunities for anyone with a PC laptop to use NodeXL in the workshop. For everyone else, there will be an opportunity to analyse and even create networks to demonstrate how SNA can be used for real world research to unlock the power of social media data. 

ABSTRACT. Before the workshop, participants are asked to register for access to the software here: http://socialdatalab.net/COSMOS

Please note that COSMOS works on Mac OS X and Ubuntu, not Windows. We are working on a web-based version to overcome these issues, and this will be released soon.

The COSMOS platform, developed and maintained by the Social Data Science Lab at Cardiff University UK (http://socialdatalab.net/), has been developed to provide non-technical researchers with easy access to Twitter data. It is available at no cost to academic and not-for-profit organisations and allows researchers to collect live data from the Twitter API either as a random 1% sample (the ‘sprinkler’) or based on specific keywords. Unlike some social media data gathering tools, COSMOS uses a visual interface, and allows researcher to filter their data further for exporting in a variety of formats. Alternatively, using its intuitive drag and drop system, users can analyse their data in the platform through plotting tweets on maps, creating graphs, visualising networks and creating word clouds. Simple sentiment analysis (using SentiStrength) is also embedded in the platform.  

In this interactive tutorial Sloan will demonstrate how to use COSMOS to: 

• Set up a Twitter data collection 
• Further refine datasets using keywords and other conditions 
• Generate a variety of visualisations including maps, charts, networks and word clouds 
• Export data for further analysis 

Participants will be encouraged to start their own collections and experiment with their own data. 
Throughout the tutorial Sloan will reflect on the strengths and weaknesses of both using Twitter data and the technical limitations of the API, based on recent research. We will also reflect on the ethical implications of using Twitter data for social research.

ABSTRACT. The tutorial will show participants what social media data are available in the web browsing history datasets on all web browsers and provide a hands-on tutorial on basic analysis of the data which can be integrated into quantitative or qualitative projects. The half-day tutorial will begin with a discussion of informed consent, featuring the data collection tool developed by Menchen-Trevino, Web Historian (2016), which was designed to collect such data using an interactive educational informed consent process and integrate multiple methods from surveys and experiments to ethnographies. Participants may use their own web browsing history in the tutorial, or a demo dataset. The tutorial will end with a broader discussion of privacy and research ethics based on our experiences analyzing our own data, and a general framework for doing so (see Menchen-Trevino, 2018). Please bring your laptop to fully participate in this workshop. For more technical details, please see this page.

ABSTRACT. This workshop follows on from two previous workshops at #SMSociety 2017 and 2018 on linking data. In 2017, we talked about what the value of linked data might be, what it might look like and what could possibly be linked. In 2018, we discussed consent rates for linked data, privacy concerns that participants in such a project might have, the vast array of data available through social media and data security issues. This year, we propose to develop the conversation further focusing on specific examples and delving deeper into the nuts and bolts of how survey and social media data can be linked, and what such linkage may actually look like.

ABSTRACT. This workshop will present tools and methods designed to bring greater transparency and user agency to data ecosystems on mobile devices. We will deploy our platform which enables access to and analysis of the coded permission of thousands of mobile apps. These have been developed across a series of Arts and Humanities Research Council UK funded cross-disciplinary research projects and in conjunction with the Berlin-based Tactical Tech Collective. Our participatory research has a simple aim: to cultivate critical understandings and literacies around the essential building blocks of datafication found on the social media mobile applications we use in everyday life. Our workshop will allow participants, regardless of their technical capacity, to examine the thousands of different Android manifests, and thus to explore the different kinds of permissions and trackers used by those apps which enable the flow of our social data to both first and third parties.

ABSTRACT. The purpose of this one-session workshop is to introduce novice and experienced researchers to social bot analysis. The participants will learn how to (1) collect Twitter data, (2) detect social bots, and (3) analyze the tweets of social bots.  This short session provides a detailed tutorial for Twitter data collection and text mining with R, and bot detection with Python. 

ABSTRACT. Participate in this workshop to learn how to use DiscoverText build custom machine classifiers for sifting free text, emails, survey responses, Twitter data, RSS feeds, and more. Each participant will receive a gratis Special Enterprise Account good for a group of 10 users for 90 days. Please email stu@texifter.com to request a license key in advance of the workshop.

The topics covered include how to:

• fetch fresh sample Twitter Search API datasets,
• construct precise or broad social data queries,
• join Twitter data research teams working on #metoo, #balancetonporc, #cuéntalo,
• respect the right to be forgotten,
• use Boolean search on raw data archives,
• filter on metadata or other project attributes,
• tabulate, explore, and set aside duplicates, cluster near-duplicates,
• crowd source human coding (annotation),
• measure and think about inter-rater reliability,
• adjudicate coder disagreements, and
• quickly build reusable word sense, language, and topic disambiguation machine classifiers.