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20162023
most citedSampling from Social Networks with Attributes

46 citations · 90 across the 8 of their papers we have counts for

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7 papers · 1 filter

cs.SI2023

You are a Bot! -- Studying the Development of Bot Accusations on Twitter

Dennis Assenmacher, Leon Fröhling, Claudia Wagner

The characterization and detection of bots with their presumed ability to manipulate society on social media platforms have been subject to many research endeavors over the last de…

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

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.SI2018

What increases (social) media attention: Research impact, author prominence or title attractiveness?

Olga Zagovora, Katrin Weller, Milan Janosov +2

Do only major scientific breakthroughs hit the news and social media, or does a 'catchy' title help to attract public attention? How strong is the connection between the importance…

cs.SI2018

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★ 46 cited

Sampling from Social Networks with Attributes

Claudia Wagner, Philipp Singer, Fariba Karimi +2

Sampling from large networks represents a fundamental challenge for social network research. In this paper, we explore the sensitivity of different sampling techniques (node sampli…