Zobrazeno 1 - 10
of 138
pro vyhledávání: '"ZHELEVA, Elena"'
In medical settings, it is critical that all who are in need of care are correctly heard and understood. When this is not the case due to prejudices a listener has, the speaker is experiencing \emph{testimonial injustice}, which, building upon recent
Externí odkaz:
http://arxiv.org/abs/2410.01227
The presence of interference, where the outcome of an individual may depend on the treatment assignment and behavior of neighboring nodes, can lead to biased causal effect estimation. Current approaches to network experiment design focus on limiting
Externí odkaz:
http://arxiv.org/abs/2405.12340
Autor:
Wentzel, Andrew, Levine, Lauren, Dhariwal, Vipul, Fatemi, Zarah, Bhattacharya, Abarai, Di Eugenio, Barbara, Rojecki, Andrew, Zheleva, Elena, Marai, G. Elisabeta
We present a visual computing framework for analyzing moral rhetoric on social media around controversial topics. Using Moral Foundation Theory, we propose a methodology for deconstructing and visualizing the \textit{when}, \textit{where}, and \texti
Externí odkaz:
http://arxiv.org/abs/2403.14696
Publikováno v:
In Proceedings of the ACM Web Conference 2024 (WWW '24), May 13-17, 2024, Singapore, Singapore. ACM, New York, NY, USA, 12 pages
While exposure to diverse viewpoints may reduce polarization, it can also have a backfire effect and exacerbate polarization when the discussion is adversarial. Here, we examine the question whether intergroup interactions around important events aff
Externí odkaz:
http://arxiv.org/abs/2402.11895
Autor:
Faruk, Ahmed Sayeed, Zheleva, Elena
Recommender systems relying on contextual multi-armed bandits continuously improve relevant item recommendations by taking into account the contextual information. The objective of these bandit algorithms is to learn the best arm (i.e., best item to
Externí odkaz:
http://arxiv.org/abs/2310.10259
Autor:
Wentzel, Andrew, Levine, Lauren, Dhariwal, Vipul, Fatemi, Zahra, Di Eugenio, Barbara, Rojecki, Andrew, Zheleva, Elena, Marai, G. Elisabeta
We describe the design process and the challenges we met during a rapid multi-disciplinary pandemic project related to stay-at-home orders and social media moral frames. Unlike our typical design experience, we had to handle a steeper learning curve,
Externí odkaz:
http://arxiv.org/abs/2308.13552
Forecasting multivariate time series data, which involves predicting future values of variables over time using historical data, has significant practical applications. Although deep learning-based models have shown promise in this field, they often
Externí odkaz:
http://arxiv.org/abs/2306.09261
Autor:
Fatemi, Zahra, Zheleva, Elena
Contagion effect refers to the causal effect of peers' behavior on the outcome of an individual in social networks. Contagion can be confounded due to latent homophily which makes contagion effect estimation very hard: nodes in a homophilic network t
Externí odkaz:
http://arxiv.org/abs/2306.02479
Autor:
Adhikari, Shishir, Zheleva, Elena
Causal inference in networks should account for interference, which occurs when a unit's outcome is influenced by treatments or outcomes of peers. Heterogeneous peer influence (HPI) occurs when a unit's outcome is influenced differently by different
Externí odkaz:
http://arxiv.org/abs/2305.17479