In an effort to clean up my reading list, this page catalogues papers that caught my eye but that I never got around to reading.
I’d love to read all of these some day; like I said, they caught my eye at least once before. But, being realistic with myself, I think it’s important to accept that I can’t get around to everything; I have limited time and energy. Rather than maintain an indefinite list of “laters,” I choose to put these papers to rest on this page.
I liken this to closing my browser tabs. If something is truly engaging, I’ll come back to it later. But for now, I am accepting that I have no plans to read these, as great as they probably are.
When looking for papers to read, I used the following sources:
- Ali Alkhatib: A (tentative) CHI Reading List
- CHI 2020 Best Papers & Honorable Mentions
- Full Proceedings
- UW Interactive Data Lab
- Twitter thread by Casey Fiesler
- Another Twitter thread by Vera Liao
- ai4hci workshop
And these all looked interesting to me:
- Wrex: A Unifed Programming-by-Example Interaction for Synthesizing Readable Code for Data Scientists by Ian Drosos, Titus Barik, Philip J. Guo, Robert DeLine, Sumit Gulwani
- A Probabilistic Grammar of Graphics (Xiaoying Pu & Matthew Kay)
- Social Comparison and Facebook (Moira Burke, Justin Cheng & Bethany de Gant)
- Characterizing Twitter Users Who Engage in Adversarial Interactions against Political Candidates (Yiqing Hua, Mor Naaman & Thomas Ristenpart)
- Questioning the AI: Informing Design Practices for Explainable AI User Experiences (Q. Vera Liao, Daniel Gruen & Sarah Miller)
- Explain like I am a Scientist: The Linguistic Barriers of Entry to r/science
- No Explainability without Accountability: An Empirical Study of Explanations and Feedback in Interactive ML
- Paths Explored, Paths Omitted, Paths Obscured: Decision Points & Selective Reporting in End-to-End Data Analysis
- Many Faced Hate: A Cross Platform Study of Content Framing and Information Sharing by Online Hate Groups
I identified these by looking through the proceedings at: https://aaai.org/ojs/index.php/ICWSM/issue/view/262.
Communal Quirks and Circlejerks: A Taxonomy of Processes Contributing to Insularity in Online Communities by Kimberley Allison, Kay Bussey
Higher Ground? How Groundtruth Labeling Impacts Our Understanding of Fake News about the 2016 U.S. Presidential Nominees by Lia Bozarth, Aparajita Saraf, Ceren Budak
Toward a Better Performance Evaluation Framework for Fake News Classification by Lia Bozarth, Ceren Budak
No Robots, Spiders, or Scrapers: Legal and Ethical Regulation of Data Collection Methods in Social Media Terms of Service by Casey Fiesler, Nathan Beard, Brian C. Keegan
Towards Measuring Adversarial Twitter Interactions against Candidates in the US Midterm Elections by Yiqing Hua, Thomas Ristenpart, Mor Naaman
Detecting Troll Behavior via Inverse Reinforcement Learning: A Case Study of Russian Trolls in the 2016 US Election by Luca Luceri, Silvia Giordano, Emilio Ferrara
The Structure of U.S. College Networks on Facebook by Jan Overgoor, Bogdan State, Lada A. Adamic
I don’t plan to read these any time soon; but again, these all looked interesting at some point.
On the Utility of Learning about Humans for Human-AI Coordination from BAIR, NeurIPS 2019
Gelman: progress from the past decade is a list of tons of papers on his blog
The stealth media? Groups and targets behind divisive issue campaigns on Facebook from Network Propaganda
Weaponizing the digital influence machine: the political perils of online ad tech on digital political advertising
From the participatory design workshop:
- Fairness, Equality, and Power in Algorithmic Decision-Making
- Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics (Encore: ICML 2020)
- The Hidden Assumptions Behind Counterfactual Explanations and Principal Reasons (Encore: FAccT 2020)
- Metric-Free Individual Fairness in Online Learning
Most things on this course project page, found from the author of the Skynet Today article
The coming software apocalypse from The Atlantic. I’ve already read this, but worth revisiting.
FAIR blog post on insta recommendations, from Miranda
An epidemic of AI misinformation from Data Elixir
Overcooked blog post by BAIR, from Judah