All

Papers

Browse and search HCI research papers from All

Active Filters

Author: 36996

12 results

What If Moderation Didn’t Mean Suppression? A Case for Personalized Content Transformation

Centralized content moderation paradigm both falls short and overreaches: 1) it fails to account for the subjective nature of harm, and 2) it acts with blunt suppression in response to content deemed harmful, even when such content can be salvaged. We first investigate this through formative interviews, documenting ho…

Rayhan Rashed et al.University of Michigan

Interpretive Cultures: Resonance, randomness, and negotiated meaning for AI-assisted tarot divination

While generative AI tools are increasingly adopted for creative and analytical tasks, their role in interpretive practices,where meaning is subjective, plural, and non-causal, remains poorly understood. This paper examines AI-assisted tarot reading, a divinatory practice in which users pose a query, draw cards through…

Matthew Kieran Prock et al.University of Michigan

Value Alignment of Social Media Ranking Algorithms

While social media feed rankings are primarily driven by engagement signals rather than any explicit value system, the resulting algorithmic feeds are not value-neutral: engagement may prioritize specific individualistic values. This paper presents an approach for social media feed value alignment. We adopt Schwartz’s…

Farnaz Jahanbakhsh et al.University of Michigan

A Browser Extension for in-place Signaling and Assessment of Misinformation

The status-quo of misinformation moderation is a central authority, usually social platforms, deciding what content constitutes misinformation and how it should be handled. However, to preserve users’ autonomy, researchers have explored democratized misinformation moderation. One proposition is to enable users to asse…

Farnaz Jahanbakhsh et al.University of Michigan

AdRecommended

Learn AI Coding at CodeNow

Structured lessons, hands-on projects, and continuous updates for people bringing AI into real development work.

Explore Now

Exploring the Use of Personalized AI for Identifying Misinformation on Social Media

This work aims to explore how human assessments and AI predictions can be combined to identify misinformation on social media. To do so, we design a personalized AI which iteratively takes as training data a single user's assessment of content and predicts how the same user would assess other content. We conduct a use…

Farnaz Jahanbakhsh et al.University of Michigan

Leveraging Structured Trusted-Peer Assessments to Combat Misinformation

Platform operators have devoted significant effort to combating misinformation on behalf of their users. Users are also stakeholders in this battle, but their efforts to combat misinformation go unsupported by the platforms. In this work, we consider three new user affordances that give social media users greater powe…

Farnaz Jahanbakhsh et al.University of Michigan

Fact Checking; Fact Checking

Spotlights: Designs for Directing Learners' Attention in a Large-Scale Social Annotation Platform

A new approach to online discussion, which situates student discussions in the margins of the course content, can enhance student engagement with course materials. However, in high-enrollment classes, the large number of comments can overwhelm and intimidate students. Some become frustrated by the volume of potential…

Jumana Almahmoud et al.Massachusetts Institute of Technology

Online Learning; Online Learning

Our Browser Extension Lets Readers Change the Headlines on News Articles, and You Won't Believe What They Did!

Headlines play a critical role in how users perceive articles. But many headline publishers craft headlines in ways that either attract clicks in an attempt to earn ad revenue, or misinform users or manipulate their opinions for malicious intents. Such headlines can do harm since many users simply skim and share head…

Farnaz Jahanbakhsh et al.University of Michigan

Fact Checking; Fact Checking

Understanding Questions that Arise When Working with Business Documents

While digital assistants are increasingly used to help with various productivity tasks, less attention has been paid to employing them in the domain of business documents. To build an agent that can handle users' information needs in this domain, we must first understand the types of assistance that users desire when…

Farnaz Jahanbakhsh et al.University of Michigan

Business Processes & Worker Advocacy; Business Processes & Worker Advocacy

Exploring Lightweight Interventions at Posting Time to Reduce the Sharing of Misinformation on Social Media

When users on social media share content without considering its veracity, they may unwittingly be spreading misinformation. In this work, we investigate the design of lightweight interventions that nudge users to assess the accuracy of information as they share it. Such assessment may deter users from posting misinfo…

Farnaz Jahanbakhsh et al.University of Michigan

Misinformation, Conspiracies, and Manipulations

An Experimental Study of Bias in Platform Worker Ratings: The Role of Performance Quality and Gender

We study how the ratings people receive on online labor platforms are influenced by their performance, gender, their rater's gender, and displayed ratings from other raters. We conducted a deception study in which participants collaborated on a task with a pair of simulated workers, who varied in gender and performanc…

Farnaz Jahanbakhsh et al.University of Michigan

Structure or Nurture? The Effects of Team-Building Activities and Team Composition on Team Outcomes

How can instructors group students into teams that interact and learn effectively together? One strand of research advocates for grouping students into teams with "good" compositions such as skill diversity. Another strand argues for deploying team-building activities to foster interpersonal relations like psychologi…

Emily M. Hastings et al.University of Illinois

Team-Based Communication

Paper Title	Authors	Research Topics
emoji_events What If Moderation Didn’t Mean Suppression? A Case for Personalized Content Transformation Centralized content moderation paradigm both falls short and overreaches: 1) it fails to account for the subjective nature of harm, and 2) it acts with blunt suppression in response to content deemed harmful, even when such content can be salvaged. We first investigate this through formative interviews, documenting ho…	RR Rayhan Rashed et al.University of Michigan
Interpretive Cultures: Resonance, randomness, and negotiated meaning for AI-assisted tarot divination While generative AI tools are increasingly adopted for creative and analytical tasks, their role in interpretive practices,where meaning is subjective, plural, and non-causal, remains poorly understood. This paper examines AI-assisted tarot reading, a divinatory practice in which users pose a query, draw cards through…	MP Matthew Kieran Prock et al.University of Michigan
Value Alignment of Social Media Ranking Algorithms While social media feed rankings are primarily driven by engagement signals rather than any explicit value system, the resulting algorithmic feeds are not value-neutral: engagement may prioritize specific individualistic values. This paper presents an approach for social media feed value alignment. We adopt Schwartz’s…	FJ Farnaz Jahanbakhsh et al.University of Michigan
A Browser Extension for in-place Signaling and Assessment of Misinformation The status-quo of misinformation moderation is a central authority, usually social platforms, deciding what content constitutes misinformation and how it should be handled. However, to preserve users’ autonomy, researchers have explored democratized misinformation moderation. One proposition is to enable users to asse…	FJ Farnaz Jahanbakhsh et al.University of Michigan
AdRecommended Learn AI Coding at CodeNow Structured lessons, hands-on projects, and continuous updates for people bringing AI into real development work. Explore Now
Exploring the Use of Personalized AI for Identifying Misinformation on Social Media This work aims to explore how human assessments and AI predictions can be combined to identify misinformation on social media. To do so, we design a personalized AI which iteratively takes as training data a single user's assessment of content and predicts how the same user would assess other content. We conduct a use…	FJ Farnaz Jahanbakhsh et al.University of Michigan
Leveraging Structured Trusted-Peer Assessments to Combat Misinformation Platform operators have devoted significant effort to combating misinformation on behalf of their users. Users are also stakeholders in this battle, but their efforts to combat misinformation go unsupported by the platforms. In this work, we consider three new user affordances that give social media users greater powe…	FJ Farnaz Jahanbakhsh et al.University of Michigan	Fact Checking; Fact Checking
Spotlights: Designs for Directing Learners' Attention in a Large-Scale Social Annotation Platform A new approach to online discussion, which situates student discussions in the margins of the course content, can enhance student engagement with course materials. However, in high-enrollment classes, the large number of comments can overwhelm and intimidate students. Some become frustrated by the volume of potential…	JA Jumana Almahmoud et al.Massachusetts Institute of Technology	Online Learning; Online Learning
Our Browser Extension Lets Readers Change the Headlines on News Articles, and You Won't Believe What They Did! Headlines play a critical role in how users perceive articles. But many headline publishers craft headlines in ways that either attract clicks in an attempt to earn ad revenue, or misinform users or manipulate their opinions for malicious intents. Such headlines can do harm since many users simply skim and share head…	FJ Farnaz Jahanbakhsh et al.University of Michigan	Fact Checking; Fact Checking
Understanding Questions that Arise When Working with Business Documents While digital assistants are increasingly used to help with various productivity tasks, less attention has been paid to employing them in the domain of business documents. To build an agent that can handle users' information needs in this domain, we must first understand the types of assistance that users desire when…	FJ Farnaz Jahanbakhsh et al.University of Michigan	Business Processes & Worker Advocacy; Business Processes & Worker Advocacy
Exploring Lightweight Interventions at Posting Time to Reduce the Sharing of Misinformation on Social Media When users on social media share content without considering its veracity, they may unwittingly be spreading misinformation. In this work, we investigate the design of lightweight interventions that nudge users to assess the accuracy of information as they share it. Such assessment may deter users from posting misinfo…	FJ Farnaz Jahanbakhsh et al.University of Michigan	Misinformation, Conspiracies, and Manipulations
An Experimental Study of Bias in Platform Worker Ratings: The Role of Performance Quality and Gender We study how the ratings people receive on online labor platforms are influenced by their performance, gender, their rater's gender, and displayed ratings from other raters. We conducted a deception study in which participants collaborated on a task with a pair of simulated workers, who varied in gender and performanc…	FJ Farnaz Jahanbakhsh et al.University of Michigan
Structure or Nurture? The Effects of Team-Building Activities and Team Composition on Team Outcomes How can instructors group students into teams that interact and learn effectively together? One strand of research advocates for grouping students into teams with "good" compositions such as skill diversity. Another strand argues for deploying team-building activities to foster interpersonal relations like psychologi…	EH Emily M. Hastings et al.University of Illinois	Team-Based Communication