Public Group active 1 week, 4 days ago

PUG – Python User’s Group

Python User’ Group (or PUG for short) is an open and informal collaborative space for experimentation and exploration with the Python programming language. It is an opportunity for those interested in Python to work together virtually and find support. Whether you are looking for advice or assistance with new or current projects, looking to discuss and learn new skills using Python tools, or to join us to play around with our collection of sample datasets, PUG is your place!

PUG is open to people of all skill levels, disciplines, and backgrounds. Complete beginners to Python will find a place here. Come, and let’s learn together.

Join PUG Slack here: https://join.slack.com/t/pug-world/shared_invite/zt-iube7uch-nVkvtIyIbpaqtQSZcMB2Ig

PUG is cosponsored by the MA in Digital Humanities / MS in Data Analytics and Visualization programs and the Mina Rees Library.

To learn more, visit http://cuny.is/pug

Admins:

This Wednesday 4-5pm: Working with social media data event

  • Please join the GC Digital Fellows, GCDI, and the M.S. in Data Analysis and Visualization in welcoming Dr. Jo Lukito (UT Austin) for a conversation focused on practical strategies for researching social media today. The event will take place virtually on Zoom on May 3rd from 4 – 5pm ET. You can register for the event here. We recommend coming prepared with questions about your own social media-based projects.

    As an expert in social media research, Dr. Jo Lukito is excited to speak with GC students and faculty about their projects and help find ways to continue using social media data despite the ongoing restrictions. Jo is an Assistant Professor at the University of Texas at Austin’s School of Journalism and Media. She is also the Director of the Media & Democracy Data Cooperative and a Senior Faculty Research Affiliate for the Center for Media Engagement. Jo uses mixed methods and computational approaches to study political language in the hybrid media ecology, focusing especially on harmful digital content (e.g., mis/disinformation, hate speech) and public sphere across multiple social media. Jo’s work has been published in both peer-reviewed journals like Political Communication and Social Media + Society and has contributed to Wired, Vox, and Columbia Journalism Review.

    This conversation is happening at a pivotal moment for social media research. Many of us who analyze Twitter data as part of our scholarly work have spent the last few months in a furry to download as many Twitter datasets as we can before we no longer have access to the archive. This race to get as much data as possible began on February 1st when Twitter announced that it will soon no longer support free access to the social media platform’s application programming interface (API). Up until then, researchers had access to the entire Twitter archive dating back to the first published tweet in 2006. Though you had to apply to be granted access to the Twitter archive, generally speaking, PhD candidates, Post Docs, and other advanced scholars with a clearly defined research project were given unfettered access to Twitter’s data with up to 10M tweet downloads per month. That’s a whole lot of data for researchers to explore critical questions about our world from culture to politics, misinformation to wellness, linguistics to internet discourse, and beyond.

    Outside of Twitter, access to data from social media platforms is slim pickings. Meta, which owns Facebook and Instagram among other platforms, keeps a tight grip on its data. That being said, Meta has been expanding the types of data it makes available to researchers through its CrowdTangle API, which prioritizes access to scholars focused on Misinformation, Elections, COVID-19, Racial justice, and Well-being. Meta has also created hundreds of datasets, mostly country-by-country population mapping and density datasets as well as some datasets of political ads and other topics of concern, that it shares via the Humanitarian Data Exchange repository (HDE). TikTok is also developing capacities for researchers to computationally collect data, but this program is still in its infancy. LinkedIn does not currently have plans to create an API for researchers. Luckily, Reddit and YouTube remain platforms with fairly robust data sharing tools, allowing researchers to study social phenomena using computational tools.

    Join us in learning more about the current and future state of social media research and ways to continue studying important scholarly questions on these platforms. We hope to see you there!

     

    Read GCDI post here!

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