activity
20162026
most citedInequality and Inequity in Network-based Ranking and Recommendation Algorithms

38 citations · 143 across the 10 of their papers we have counts for

collaborators

10 papers

cs.IR2026

Whose Name Comes Up? II: Benchmarking and Intervention-Based Auditing of LLM-Based Scholar Recommendation

Lisette Espín-Noboa, Gonzalo Gabriel Méndez

Large language models (LLMs) are now used for academic expert recommendation. Existing audits typically evaluate such recommendations in isolation, ignoring end-user inference-time…

cs.SI2023★ 23 cited

Social network modeling and applications, a tutorial

Lisette Espín-Noboa, Tiago Peixoto, Fariba Karimi

Social networks have been widely studied over the last century from multiple disciplines to understand societal issues such as inequality in employment rates, managerial performanc…

cs.LG2023★ 6 cited

Interpreting wealth distribution via poverty map inference using multimodal data

Lisette Espín-Noboa, János Kertész, Márton Karsai

Poverty maps are essential tools for governments and NGOs to track socioeconomic changes and adequately allocate infrastructure and services in places in need. Sensor and online cr…

cs.SI2022★ 21 cited

Link recommendations: Their impact on network structure and minorities

Antonio Ferrara, Lisette Espín-Noboa, Fariba Karimi +1

Network-based people recommendation algorithms are widely employed on the Web to suggest new connections in social media or professional platforms. While such recommendations bring…

cs.SI2021★ 38 cited

Inequality and Inequity in Network-based Ranking and Recommendation Algorithms

Lisette Espín-Noboa, Claudia Wagner, Markus Strohmaier +1

Though algorithms promise many benefits including efficiency, objectivity and accuracy, they may also introduce or amplify biases. Here we study two well-known algorithms, namely P…

cs.SI2019★ 4 cited

HopRank: How Semantic Structure Influences Teleportation in PageRank (A Case Study on BioPortal)

Lisette Espín-Noboa, Florian Lemmerich, Simon Walk +2

This paper introduces HopRank, an algorithm for modeling human navigation on semantic networks. HopRank leverages the assumption that users know or can see the whole structure of t…

cs.SI2018★ 10 cited

Towards Quantifying Sampling Bias in Network Inference

Lisette Espín-Noboa, Claudia Wagner, Fariba Karimi +1

Relational inference leverages relationships between entities and links in a network to infer information about the network from a small sample. This method is often used when glob…

cs.SI2017

Characterizing Information Diets of Social Media Users

Juhi Kulshrestha, Muhammad Bilal Zafar, Lisette Espin-Noboa +2

With the widespread adoption of social media sites like Twitter and Facebook, there has been a shift in the way information is produced and consumed. Earlier, the only producers of…

cs.SI2016★ 12 cited

How Users Explore Ontologies on the Web: A Study of NCBO's BioPortal Usage Logs

Simon Walk, Lisette Espín-Noboa, Denis Helic +2

Ontologies in the biomedical domain are numerous, highly specialized and very expensive to develop. Thus, a crucial prerequisite for ontology adoption and reuse is effective suppor…

cs.SI2016★ 29 cited

Discovering and Characterizing Mobility Patterns in Urban Spaces: A Study of Manhattan Taxi Data

Lisette Espín-Noboa, Florian Lemmerich, Philipp Singer +1

Nowadays, human movement in urban spaces can be traced digitally in many cases. It can be observed that movement patterns are not constant, but vary across time and space. In this…