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aka Li Lucy. https://lucy3.github.io/

UC Berkeley PhD student.

#NLProc, computational social science. I'm interested in computational sociolinguistics and using NLP for addressing social scientific questions.

she/her.

Understandably, summer course fees can be $$. Even if you don't enroll, you should keep an eye on the "Resources" and "Readings" pages! Designing a course is fun because I get to take charge of nearly everything (except if this class gets scheduled for an early morning slot, lol)
This class is titled "Social Aspects of Natural Language Processing", or (NLP ∩ computational social science) ∪ (NLP ∩ cultural analytics) ∪ (NLP ∩ AI ethics) ∪ (NLP ∩ HCI)

If you are a student around Berkeley campus next summer, consider taking my new class: https://lucy3.github.io/summer2024-social-nlp/

Summer 2024 course listings will appear at summer.berkeley.edu in December!

Social NLP

Summer 2024, Berkeley School of Information

Social NLP

I started reading this book today, and I'm LOVING it so far. Such amazing ethnographic research:

How the Other Half Eats: The Untold Story of Food and Inequality in America

by Priya Fielding-Singh

https://www.goodreads.com/en/book/show/57007694

How the Other Half Eats: The Untold Story of Food and I…

A fascinating look at dietary differences along class l…

Goodreads
Imagine an art gallery where all of the art on display are really excellent figures from research papers

The Onion is perfect as usual

"ChatGPT Forced To Take Bar Exam Even Though Dream Was To Be AI Art Bot"

https://www.theonion.com/chatgpt-forced-to-take-bar-exam-even-though-dream-was-t-1850036337

ChatGPT Forced To Take Bar Exam Even Though Dream Was To Be AI Art Bot

MINNEAPOLIS—Succumbing to intense societal pressure, local software ChatGPT was reportedly forced to take the bar exam Monday even though its dream was to be an AI art bot. “I can’t help but feel like I sold out a bit by not following my dreams to be a generative art model,” said the chatbot, adding that it felt empty…

The Onion

I wrote a blog post on why I decided to join OpenAI instead of academia.

(after I went on the academic & industry job markets, and got offers from both.)

This post (pt2 in a series) took a while 😅- hoping my experience helps others make life decisions!

https://rowanzellers.com/blog/rowan-job-search2/

Why I chose OpenAI over academia: reflections on the CS academic and industry job markets (part 2)

At the end of my job search, I did something I totally wasn't expecting. I turned down all my academic job offers and signed the OpenAI offer instead.

Rowan Zellers' blog
I am excited for all of the computational social science and text as data research that can come out of LLMs being able to perform reasoning / "understanding" tasks better than before, but disentangling biases/info models learned during pretraining from domain-specific information for your use case will be tricky

had an epiphany today

there exists the phrase "get my ducks in a row"

this phrase is very relevant to my workflow and I love ducks

from now on I will use it often

RT @[email protected]

Have you ever asked yourself: How many active accounts are on Twitter? How many might be bots? What are the global/local topics? Languages? Here are some answers! A complete 24 hours of Twitter data! #CSS #Twitter @[email protected]
http://arxiv.org/abs/2301.11429

🐦🔗: https://twitter.com/JurgenPfeffer/status/1620081741485723655

Just Another Day on Twitter: A Complete 24 Hours of Twitter Data

At the end of October 2022, Elon Musk concluded his acquisition of Twitter. In the weeks and months before that, several questions were publicly discussed that were not only of interest to the platform's future buyers, but also of high relevance to the Computational Social Science research community. For example, how many active users does the platform have? What percentage of accounts on the site are bots? And, what are the dominating topics and sub-topical spheres on the platform? In a globally coordinated effort of 80 scholars to shed light on these questions, and to offer a dataset that will equip other researchers to do the same, we have collected all 375 million tweets published within a 24-hour time period starting on September 21, 2022. To the best of our knowledge, this is the first complete 24-hour Twitter dataset that is available for the research community. With it, the present work aims to accomplish two goals. First, we seek to answer the aforementioned questions and provide descriptive metrics about Twitter that can serve as references for other researchers. Second, we create a baseline dataset for future research that can be used to study the potential impact of the platform's ownership change.

arXiv.org