Krishna P Gummadi
Biographic Data
| ID | 4987667 |
|---|---|
| NAME | Krishna P Gummadi |
| GIVEN NAMES | Krishna P |
| FAMILY NAME | Gummadi |
| SIGNATURE | GUMMADI K P |
| AFFILIATIONS | Max Planck Institute for Software Systems |
| ORCID | 0000-0003-1256-8800 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 41 |
| WORKS AS AUTHOR | 7 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2007 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 1 |
Antitrust, Amazon, and Algorithmic Auditing
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 life. Unlike traditional markets, market participant behavior is easily observable in these markets. We present a series of empirical investigations into the extent to which Amazon engages in practices that are typically described as self-preferencing. We discuss how th…
FaiRIR
Related item recommendations (RIRs) are ubiquitous in most online platforms today, including e-commerce and content streaming sites. These recommendations not only help users compare items related to a given item but also play a major role in bringing traffic to individual items, thus deciding the exposure that different items receive. With a growing number of people depending on such platforms to earn their livelihood, it is important to underst…
Analyzing Biases in Perception of Truth in News Stories and Their Implications for Fact Checking
Misinformation on social media has become a critical problem, particularly during a public health pandemic. Most social platforms today rely on users’ voluntary reports to determine which news stories to fact-check first. Despite the importance, no prior work has explored the potential biases in such a reporting process. This work proposes a novel methodology to assess how users perceive truth or misinformation in online news stories. By conducti…
Message Impartiality in Social Media Discussions
Discourse on social media platforms is often plagued by acute polarization, with different camps promoting different perspectives on the issue at hand—compare, for example, the differences in the liberal and conservative discourse on the U.S. immigration debate. A large body of research has studied this phenomenon by focusing on the affiliation of groups and individuals. We propose a new finer-grained perspective: studying the impartiality of ind…
Leveraging Facebook's Advertising Platform to Monitor Stocks of Migrants
Measuring User Influence in Twitter
Directed links in social media could represent anything from intimate friendships to common interests, or even a passion for breaking news or celebrity gossip. Such directed links determine the flow of information and hence indicate a user's influence on others — a concept that is crucial in sociology and viral marketing. In this paper, using a large amount of data collected from Twitter, we present an in-depth comparison of three measures of inf…
Measurement and analysis of online social networks
Online social networking sites like Orkut, YouTube, and Flickr are among the most popular sites on the Internet. Users of these sites form a social network, which provides a powerful means of sharing, organizing, and finding content and contacts. The popularity of these sites provides an opportunity to study the characteristics of online social network graphs at large scale. Understanding these graphs is important, both to improve current systems…
Measurement and analysis of online social networks
Online social networking sites like Orkut, YouTube, and Flickr are among the most popular sites on the Internet. Users of these sites form a social network, which provides a powerful means of sharing, organizing, and finding content and contacts. The popularity of these sites provides an opportunity to study the characteristics of online social network graphs at large scale. Understanding these graphs is important, both to improve current systems…
Measuring User Influence in Twitter
Directed links in social media could represent anything from intimate friendships to common interests, or even a passion for breaking news or celebrity gossip. Such directed links determine the flow of information and hence indicate a user's influence on others — a concept that is crucial in sociology and viral marketing. In this paper, using a large amount of data collected from Twitter, we present an in-depth comparison of three measures of inf…
Leveraging Facebook's Advertising Platform to Monitor Stocks of Migrants
Message Impartiality in Social Media Discussions
Discourse on social media platforms is often plagued by acute polarization, with different camps promoting different perspectives on the issue at hand—compare, for example, the differences in the liberal and conservative discourse on the U.S. immigration debate. A large body of research has studied this phenomenon by focusing on the affiliation of groups and individuals. We propose a new finer-grained perspective: studying the impartiality of ind…
Analyzing Biases in Perception of Truth in News Stories and Their Implications for Fact Checking
Misinformation on social media has become a critical problem, particularly during a public health pandemic. Most social platforms today rely on users’ voluntary reports to determine which news stories to fact-check first. Despite the importance, no prior work has explored the potential biases in such a reporting process. This work proposes a novel methodology to assess how users perceive truth or misinformation in online news stories. By conducti…
FaiRIR
Related item recommendations (RIRs) are ubiquitous in most online platforms today, including e-commerce and content streaming sites. These recommendations not only help users compare items related to a given item but also play a major role in bringing traffic to individual items, thus deciding the exposure that different items receive. With a growing number of people depending on such platforms to earn their livelihood, it is important to underst…
Antitrust, Amazon, and Algorithmic Auditing
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 life. Unlike traditional markets, market participant behavior is easily observable in these markets. We present a series of empirical investigations into the extent to which Amazon engages in practices that are typically described as self-preferencing. We discuss how th…
Computer Science (6 works) · World Wide Web (5 works) · Social media (4 works) · Business (3 works) · Complex Network Analysis Techniques (3 works) · Data science (3 works) · Opinion Dynamics and Social Influence (3 works) · Psychology (3 works) · Social Psychology (3 works) · Sociology (3 works)