192 citations · 338 across the 27 of their papers we have counts for
28 papers
Characterizing Bluesky Content Moderation Service: From Automation of Service to Landscape of Harms
Pushpdeep Singh, Sayeh Jarollahi, Ayan Majumdar +5
Empirical research on content moderation is fundamentally constrained by the opaque deployment of moderation systems on major social media platforms. To this end, the recent emerge…
RSTGCN: Railway-centric Spatio-Temporal Graph Convolutional Network for Train Delay Prediction
Koyena Chowdhury, Paramita Koley, Abhijnan Chakraborty +1
Accurate prediction of train delays is critical for efficient railway operations. While earlier approaches have largely focused on forecasting the exact delays of individual trains…
Sponsored is the New Organic: Implications of Sponsored Results on Quality of Search Results in the Amazon Marketplace
Abhisek Dash, Saptarshi Ghosh, Animesh Mukherjee +2
Interleaving sponsored results (advertisements) amongst organic results on search engine result pages (SERP) has become a common practice across multiple digital platforms. Adverti…
Investigating Nudges toward Related Sellers on E-commerce Marketplaces: A Case Study on Amazon
Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh +2
E-commerce marketplaces provide business opportunities to millions of sellers worldwide. Some of these sellers have special relationships with the marketplace by virtue of using th…
Antitrust, Amazon, and Algorithmic Auditing
Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh +4
In digital markets, antitrust law and special regulations aim to ensure that markets remain competitive despite the dominating role that digital platforms play today in everyone's…
Towards Fair Allocation in Social Commerce Platforms
Anjali Gupta, Shreyans J. Nagori, Abhijnan Chakraborty +5
Social commerce platforms are emerging businesses where producers sell products through re-sellers who advertise the products to other customers in their social network. Due to the…
Gigs with Guarantees: Achieving Fair Wage for Food Delivery Workers
Ashish Nair, Rahul Yadav, Anjali Gupta +3
With the increasing popularity of food delivery platforms, it has become pertinent to look into the working conditions of the 'gig' workers in these platforms, especially providing…
These Deals Won't Last! Longevity, Uniformity and Bias in Product Badge Assignment in E-Commerce Platforms
Archit Bansal, Kunal Banerjee, Abhijnan Chakraborty
Product badges are ubiquitous in e-commerce platforms, acting as effective psychological triggers to nudge customers to buy specific products, boosting revenues. However, to the be…
Scheduling Virtual Conferences Fairly: Achieving Equitable Participant and Speaker Satisfaction
Gourab K. Patro, Prithwish Jana, Abhijnan Chakraborty +2
Recently, almost all conferences have moved to virtual mode due to the pandemic-induced restrictions on travel and social gathering. Contrary to in-person conferences, virtual conf…
FairFoody: Bringing in Fairness in Food Delivery
Anjali Gupta, Rahul Yadav, Ashish Nair +3
Along with the rapid growth and rise to prominence of food delivery platforms, concerns have also risen about the terms of employment of the gig workers underpinning this growth. O…
FaiRIR: Mitigating Exposure Bias from Related Item Recommendations in Two-Sided Platforms
Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh +2
Related Item Recommendations (RIRs) are ubiquitous in most online platforms today, including e-commerce and content streaming sites. These recommendations not only help users compa…
Alexa, in you, I trust! Fairness and Interpretability Issues in E-commerce Search through Smart Speakers
Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh +2
In traditional (desktop) e-commerce search, a customer issues a specific query and the system returns a ranked list of products in order of relevance to the query. An increasingly…
Towards Fair Recommendation in Two-Sided Platforms
Arpita Biswas, Gourab K Patro, Niloy Ganguly +2
Many online platforms today (such as Amazon, Netflix, Spotify, LinkedIn, and AirBnB) can be thought of as two-sided markets with producers and customers of goods and services. Trad…
When the Umpire is also a Player: Bias in Private Label Product Recommendations on E-commerce Marketplaces
Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh +2
Algorithmic recommendations mediate interactions between millions of customers and products (in turn, their producers and sellers) on large e-commerce marketplaces like Amazon. In…
Fairness for Whom? Understanding the Reader's Perception of Fairness in Text Summarization
Anurag Shandilya, Abhisek Dash, Abhijnan Chakraborty +2
With the surge in user-generated textual information, there has been a recent increase in the use of summarization algorithms for providing an overview of the extensive content. Tr…
Analyzing 'Near Me' Services: Potential for Exposure Bias in Location-based Retrieval
Ashmi Banerjee, Gourab K Patro, Linus W. Dietz +1
The proliferation of smartphones has led to the increased popularity of location-based search and recommendation systems. Online platforms like Google and Yelp allow location-based…
On Fair Virtual Conference Scheduling: Achieving Equitable Participant and Speaker Satisfaction
Gourab K Patro, Abhijnan Chakraborty, Niloy Ganguly +1
The (COVID-19) pandemic-induced restrictions on travel and social gatherings have prompted most conference organizers to move their events online. However, in contrast to physical…
FairRec: Two-Sided Fairness for Personalized Recommendations in Two-Sided Platforms
Gourab K Patro, Arpita Biswas, Niloy Ganguly +2
We investigate the problem of fair recommendation in the context of two-sided online platforms, comprising customers on one side and producers on the other. Traditionally, recommen…
Minimizing Margin of Victory for Fair Political and Educational Districting
Ana-Andreea Stoica, Abhijnan Chakraborty, Palash Dey +1
In many practical scenarios, a population is divided into disjoint groups for better administration, e.g., electorates into political districts, employees into departments, student…
Incremental Fairness in Two-Sided Market Platforms: On Smoothly Updating Recommendations
Gourab K Patro, Abhijnan Chakraborty, Niloy Ganguly +1
Major online platforms today can be thought of as two-sided markets with producers and customers of goods and services. There have been concerns that over-emphasis on customer sati…
On the Fairness of Time-Critical Influence Maximization in Social Networks
Junaid Ali, Mahmoudreza Babaei, Abhijnan Chakraborty +3
Influence maximization has found applications in a wide range of real-world problems, for instance, viral marketing of products in an online social network, and information propaga…
Public Sphere 2.0: Targeted Commenting in Online News Media
Ankan Mullick, Sayan Ghosh, Ritam Dutt +2
With the increase in online news consumption, to maximize advertisement revenue, news media websites try to attract and retain their readers on their sites. One of the most effecti…
Equality of Voice: Towards Fair Representation in Crowdsourced Top-K Recommendations
Abhijnan Chakraborty, Gourab K Patro, Niloy Ganguly +2
To help their users to discover important items at a particular time, major websites like Twitter, Yelp, TripAdvisor or NYTimes provide Top-K recommendations (e.g., 10 Trending Top…
Summarizing User-generated Textual Content: Motivation and Methods for Fairness in Algorithmic Summaries
Abhisek Dash, Anurag Shandilya, Arindam Biswas +3
As the amount of user-generated textual content grows rapidly, text summarization algorithms are increasingly being used to provide users a quick overview of the information conten…