Arshia Arya

dblp:284/9104 · DBLP profile ↗
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7ranked-venue papers
3as first author
7since 2021 · last 2026
0000-0002-8043-4196ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 4 · 3 first-author · 4 since 2021Artificial intelligence and machine learning · 3 · 2 first-author · 3 since 2021Applied, interdisciplinary, general and emerging computing · 3 · 1 first-author · 3 since 2021Databases, data management, data science and information retrieval · 2 · 1 first-author · 2 since 2021
YearPublicationVenuePosition
2026 Long Story Short: Auditing U.S. Political Polarization in Recommendations for Long- vs. Short-form Videos on YouTube
abstract
YouTube is the world's most widely used video platform, with over 70% of content viewed through algorithmic recommendations. While prior audits have examined polarization in YouTube's long-form video recommendations, the platform's fast-growing Shorts feature remains understudied. In this paper, we present the first large-scale audit comparing political content exposure and engagement dynamics across short-form and long-form videos on YouTube. We design a matched audit based on the insight that many news media organizations publish both short and long versions of the same content and collect 50,000 pairs of long-form and short-form video recommendations from both political and nonpolitcal seed videos. We analyze recommendations along several dimensions: the frequency of political recommendations, the diversity of retrieved videos, the engagement those videos receive, and finally, the partisan alignment between recommended videos and seed videos. Our results highlight fundamental differences between each algorithm, which we hope we can inform future research in analyzing the impact of YouTube recommendations.
Shaokang Jiang, Arshia Arya, Seoyoung Kweon, Ivan Liang, Deepak Kumar 0006, Kristen Vaccaro
WWW2
2025 Stop the Nonconsensual Use of Nude Images in Research
abstract
In order to train, test, and evaluate nudity detection models, machine learning researchers typically rely on nude images scraped from the Internet. Our research finds that this content is collected and, in some cases, subsequently \emph{distributed} by researchers without consent, leading to potential misuse and exacerbating harm against the subjects depicted. \textbf{This position paper argues that the distribution of nonconsensually collected nude images by researchers perpetuates image-based sexual abuse and that the machine learning community should stop the nonconsensual use of nude images in research.} To characterize the scope and nature of this problem, we conducted a systematic review of papers published in computing venues that collect and use nude images. Our results paint a grim reality: norms around the usage of nude images are sparse, leading to a litany of problematic practices like distributing and publishing nude images with uncensored faces, and intentionally collecting and sharing abusive content. We conclude with a call-to-action for publishing venues and a vision for research in nudity detection that balances user agency with concrete research objectives.
Princessa Cintaqia, Arshia Arya, Elissa M. Redmiles, Deepak Kumar 0006, Allison McDonald, Lucy Qin
NeurIPS2
2024 Redesigning Privacy with User Feedback: The Case of Zoom Attendee Attention Tracking
abstract
Software engineers’ unawareness of user feedback in earlier stages of design contributes to privacy issues in many products. Although extensive research exists on gathering and analyzing user feedback, there is limited understanding about how developers can integrate user feedback to improve product designs to better meet users’ privacy expectations. We use Zoom’s deprecated attendee attention tracking feature to explore issues with integrating user privacy feedback into software development, presenting public online critiques about this deprecated feature to 18 software engineers in semi-structured interviews and observing how they redesign this feature. Our results suggest that while integrating user feedback for privacy is potentially beneficial, it’s also fraught with challenges of polarized design suggestions, confirmation bias, and limited scope of perceived responsibility.
Tony W. Li, Arshia Arya, Haojian Jin
CHI2
2022 Poster: Leveraging Question Answering to Understand Context Specific Patterns in Fact Checked Articles in the Global South
abstract
Propagation of misinformation on various social media platforms is a common occurrence, especially around political events, religious beliefs, and public health. Fact checked articles, which investigate the credibility of dubious claims online, provide a reliable source of debunked misinformation. However, existing (older) fact checked articles remain an underutilized resource for understanding patterns in fake stories. We propose the use of Question Answering (QA) for analysing fact checked articles for systematically extracting metadata, potentially useful for downstream tasks such as misinformation detection, using a range of simple to nuanced questions. We find that the method gives us a context-specific understanding of common patterns and themes in misinformation, which is especially important in the Global South, where misinformation is layered with propagandist underpinning. Our findings suggest that this method can be extended by fine tuning on any event specific data set of fact checked articles to yield more robust and accurate results.
Arshia Arya, Saloni Dash, Syeda Zainab Akbar, Joyojeet Pal, Anirban Sen
COMPASS1
2022 Closed Ranks: The Discursive Value of Military Support for Indian Politicians on Social Media
abstract
Influencers play a crucial role in shaping public narratives through information creation and diffusion in the Global South. While public figures from various walks of life and their impact on public discourse have been studied, defence veterans as influencers of the political discourse have been largely overlooked. Veterans matter in the public spehere as a normatively important political lobby. They are also interesting because, unlike active-duty military officers, they are not restricted from taking public sides on politics, so their posts may provide a window into the views of those still in the service. In this work, we systematically analyze the engagement on Twitter of self-described defence-related accounts and politician accounts that post on defence-related issues. We find that self-described defence-related accounts disproportionately engage with the current ruling party in India. We find that politicians promote their closeness to the defence services and nationalist credentials through engagements with defence-related influencers. We briefly consider the institutional implications of these patterns and connections.
Agrima Seth, Soham De, Arshia Arya, Steven Wilkinson, Sushant Singh, Joyojeet Pal
ICTD3
2022 DISMISS: Database of Indian Social Media Influencers on Twitter
Arshia Arya, Soham De, Dibyendu Mishra, Gazal Shekhawat, Anmol Panda, Faisal M. Lalani, Parantak Singh, Ramaravind Kommiya Mothilal, Rynaa Grover, Sachita Nishal, Saloni Dash, Shehla Rashid Shora, Syeda Zainab Akbar, Joyojeet Pal
ICWSM1
2021 Beyond Business: A Poster Contrasting CEO Activism on Social Media in India and the United States
abstract
We studied the Twitter activity of business leaders of top 250 companies in India and the US between January, 2019 and May, 2021 and looked for trends related to cause-related messaging through a topical analysis of their tweets. Using a Word2Vec bag of words model for textual classification, we quantified their engagement with socio-political messaging, using keywords related to the United Nations Sustainable Development Goals (UN SDGs). We found that messaging on themes that have widespread social purchase and are not politically sensitive is relatively comparable across the two countries, but that results differ vastly on issues of political sensitivity. Our results point at the complex relationship between business and politics in the two countries, and the growing importance of social media in signalling those. We conclude by pointing out the importance of these findings for political science and policy research and by highlighting the scope for future work in this area.
Arshia Arya, Shehla Rashid Shora, Joyojeet Pal
COMPASS1