Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Johan Ugander"'
Autor:
William Cai, Johan Ugander
Publikováno v:
Proceedings of the International AAAI Conference on Web and Social Media. 15:95-104
Social interactions between people are a central mechanism by which behavior spreads. Several field studies have shown how observing peer behavior affects ones own behavior in a wide range of domains including health, information diffusion, advertise
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::79680309c486228048c5be1b15171db8
https://doi.org/10.1609/icwsm.v15i1.18044
https://doi.org/10.1609/icwsm.v15i1.18044
Autor:
Kristen M. Altenburger, Johan Ugander
Publikováno v:
Proceedings of the International AAAI Conference on Web and Social Media. 15:38-48
Node attribute prediction tasks arise in a wide range of classification tasks on social networks. Examples include detecting spam accounts, identifying compromised accounts, and inferring user demographics for targeted marketing. Despite the prevalen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42c2f68bb72c1457b72814b3b2596dc3
https://doi.org/10.1609/icwsm.v15i1.18039
https://doi.org/10.1609/icwsm.v15i1.18039
Autor:
Jonas L. Juul, Johan Ugander
Publikováno v:
Proc Natl Acad Sci U S A
Do some types of information spread faster, broader, or further than others? To understand how information diffusions differ, scholars compare structural properties of the paths taken by content as it spreads through a network, studying so-called cas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8273e9c50ffc4826563e2757d43b5236
https://doi.org/10.1073/pnas.2100786118
https://doi.org/10.1073/pnas.2100786118
Autor:
Samir Khan, Johan Ugander
Inverse probability weighting (IPW) is a general tool in survey sampling and causal inference, used both in Horvitz-Thompson estimators, which normalize by the sample size, and H\'ajek/self-normalized estimators, which normalize by the sum of the inv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::002a5eae02e845ce7d73ebeef2466c7f
Publikováno v:
KDD
Standard methods in preference learning involve estimating the parameters of discrete choice models from data of selections (choices) made by individuals from a discrete set of alternatives (the choice set). While there are many models for individual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1873d05f499985121719fa6a37af6d0
Autor:
Serina Chang, Johan Ugander
Recommender systems are central to modern online platforms, but a popular concern is that they may be pulling society in dangerous directions (e.g., towards filter bubbles). However, a challenge with measuring the effects of recommender systems is ho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a70aa6fc9bc2d99e99e81f5b93e73c27
Autor:
Johan Ugander, Amel Awadelkarim
Publikováno v:
KDD
Balanced graph partitioning is a critical step for many large-scale distributed computations with relational data. As graph datasets have grown in size and density, a range of highly-scalable balanced partitioning algorithms have appeared to meet var
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d817ee2e0da5421bd51f1ceac807e92e
https://doi.org/10.1145/3394486.3403239
https://doi.org/10.1145/3394486.3403239
Publikováno v:
KDD
Many prediction problems on social networks, from recommendations to anomaly detection, can be approached by modeling network data as a sequence of relational events and then leveraging the resulting model for prediction. Conditional logit models of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dfd5b5307458bd137ee042620010d3c8
Autor:
Johan Ugander, Arjun Seshadri
Publikováno v:
EC
The Multinomial Logit (MNL) model and the axiom it satisfies, the Independence of Irrelevant Alternatives (IIA), are together the most widely used tools of discrete choice. The MNL model serves as the workhorse model for a variety of fields, but is a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2529132c374a394e4a6e6b4ba0167796
Recent work studying triadic closure in undirected graphs has drawn attention to the distinction between measures that focus on the “center” node of a wedge (i.e., length-2 path) versus measures that focus on the “initiator,” a distinction wi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6dbcfe99d2fdbd4665d3b6241f10080e
http://arxiv.org/abs/1905.10683
http://arxiv.org/abs/1905.10683