Haroon

Computer Science PhD at UC Davis.

[Haroon @mharoon_]

@MaazBinMusa Did your fine-tuning crash OpenAI?

[Haroon @mharoon_]

🚨🎉 Exciting news! Our paper on algorithmic vs. user nudges for increasing news consumption on YouTube was just published at @PNASNexus
w/ @imxudong, @mwojcieszak, @erickaakcire

[PNAS Nexus @PNASNexus]

By tweaking the input to YouTube’s algorithm, researchers were able to increase how much news study participants watched on the platform. However, these changes in viewing habits didn’t change participants’ democratic attitudes or beliefs. In PNAS Nexus: https://t.co/Vw0llVdAd4

[Haroon @mharoon_]

@manoelribeiro @PrincetonCS @PrincetonCITP Congrats Manoel! 🎉

[Jonathan Stray @jonathanstray]

We asked you to submit prototype social media algorithms to be tested, and you did!
We had 21 strong entries, and our judges have chosen nine finalists. These include adding credible news, bridging-based ranking, downranking toxicity, and more.
https://t.co/TJ9nxG7e0a

[Hadi Askari @hadiaskari67]

New Preprint 🚨: Read our new paper: https://t.co/KWnhWZskPN where we try to answer the question: Can we leverage LLMs and realistic bot accounts to incentivize users to consume more news content? More below👇[1/6]

[Haroon @mharoon_]

@dggoldst @jakehofman @DavMicRot Interested!

[Zubair Shafiq @zubair_shafiq]

YouTube, the Great Radicalizer? There's an ongoing debate as to whether YouTube has a tendency to make problematic recommendations (think extreme, radicalizing, etc). We share our findings in our new @PNASNews paper https://t.co/1voGVQaL2O [w/ @mharoon_ @mwojcieszak et al]

[Magdalena Wojcieszak @mwojcieszak]

Interested in algorithms, rabbit holes, radicalization? 👇Auditing YouTube's Recommendation System for Ideologically Congenial, Extreme, and Problematic Recommendations is finally out in @PNASNews https://t.co/8ixZYHCD3L
Long hrs over 2+ yrs w/@mharoon_ @zubair_shafiq @prasantm

[Haroon @mharoon_]

🎉My paper on #auditing #YouTube for ideologically congenial, extreme, and problematic #recommendations has now been published and can be accessed at
@PNASNews.
Long time coming.🙂
https://t.co/iFW6SvcQv8

[Haroon @mharoon_]

Chatted with @levanhieu about his research on automated filter rule generation for ad-blocking on this week's episode of @__NothingToHide. Interesting stuff!

[Nothing to hide @__NothingToHide]

This week we sit with Hieu to discuss his latest research. Tune in to know more! https://t.co/OJ9FxgdsTt

[Yash Vekaria @vekariayash]

My first PhD paper: "The Inventory is Dark and Full of Misinformation: Understanding the Abuse of Ad Inventory Pooling in the Ad-Tech Supply Chain" (@zubair_shafiq, @rishabn_) got accepted (shepherding) to @IEEESSP 🎉. Stay tuned for details. More works to unravel in this space.

[Reece Peck @PeckReece]

Interesting tool/website developed by @mharoon_ and his team for visualizing how YouTube's algorithm reinforces political bias. I've been playing with it & the "left" side STILL promotes Fox News videos, something I observed firsthand. https://t.co/sHAjAsNeTr

[Haroon @mharoon_]

🎉 Excited to share that my first-authored paper on Ideological Congeniality in YouTube recommendations has been accepted @PNASNews. It's been an exciting journey with excellent reviewer feedback.
w/ @nshuman_chhabra, @mwojcieszak, @zubair_shafiq, @xinliuucdavise1, @prasantm

[Nothing to hide @__NothingToHide]

This week in a special episode with @atmarkopoulou , @zubair_shafiq , @proffnes , and @nlaout from @proper_data Frontier Project, we unpack the current state of user privacy on the internet and explore the path forward!

Tune in to listen:
https://t.co/f4cOReW2XP

[Magdalena Wojcieszak @mwojcieszak]

The great @imxudong presenting #ICA23: unobtrusive nudges to #YouTube #algorithm increase recommendations *and* exposure to news, *and* diversifies recommendations and exposure for Strong Conservatives. Nudges to users do nothing. with @mharoon_ @erickaakcire

[Haroon @mharoon_]

@imxudong @UNDCommDept Congratulations!

[Manoel @manoelribeiro]

New preprint 🚨
We show that recommender system audits are of limited utility in determining the prevalence of phenomena like radicalization, rabbit holes, etc., if they do not model how users interact with algorithms (which no one really does!)

📰: https://t.co/Gyvc3rOaJm

[Haroon @mharoon_]

💯

[Rong Ching Chang @AnnCC12]

News coverage of my group on our research focuses of good ai vs bad ai by @UCDavisCOE
https://t.co/Gq4OOHsUtC

[Nothing to hide @__NothingToHide]

We are very excited to launch Nothing to hide? A data privacy podcast! https://t.co/OJ9FxgdsTt