Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Juneja, Prerna"'
Despite being an integral tool for finding health-related information online, YouTube has faced criticism for disseminating COVID-19 misinformation globally to its users. Yet, prior audit studies have predominantly investigated YouTube within the Glo
Externí odkaz:
http://arxiv.org/abs/2409.10168
As more users turn to video-sharing platforms like YouTube as an information source, they may consume misinformation despite their best efforts. In this work, we investigate ways that users can better assess the credibility of videos by first explori
Externí odkaz:
http://arxiv.org/abs/2402.17218
Autor:
Juneja, Prerna, Zhang, Wenjuan, Smith-Renner, Alison Marie, Lamba, Hemank, Tetreault, Joel, Jaimes, Alex
There is a growing demand for transparency in search engines to understand how search results are curated and to enhance users' trust. Prior research has introduced search result explanations with a focus on how to explain, assuming explanations are
Externí odkaz:
http://arxiv.org/abs/2401.16509
With the 2022 US midterm elections approaching, conspiratorial claims about the 2020 presidential elections continue to threaten users' trust in the electoral process. To regulate election misinformation, YouTube introduced policies to remove such co
Externí odkaz:
http://arxiv.org/abs/2302.07836
Autor:
Juneja, Prerna, Mitra, Tanushree
Increasing demands for fact-checking has led to a growing interest in developing systems and tools to automate the fact-checking process. However, such systems are limited in practice because their system design often does not take into account how f
Externí odkaz:
http://arxiv.org/abs/2205.10894
Autor:
Juneja, Prerna, Mitra, Tanushree
In this position paper, we propose the use of existing XAI frameworks to design interventions in scenarios where algorithms expose users to problematic content (e.g. anti vaccine videos). Our intervention design includes facts (to indicate algorithmi
Externí odkaz:
http://arxiv.org/abs/2202.02479
Autor:
Juneja, Prerna, Mitra, Tanushree
Publikováno v:
CHI Conference on Human Factors in Computing Systems 2021
There is a growing concern that e-commerce platforms are amplifying vaccine-misinformation. To investigate, we conduct two-sets of algorithmic audits for vaccine misinformation on the search and recommendation algorithms of Amazon -- world's leading
Externí odkaz:
http://arxiv.org/abs/2101.08419
Issue Tracking Systems (ITS) such as Bugzilla can be viewed as Process Aware Information Systems (PAIS) generating event-logs during the life-cycle of a bug report. Process Mining consists of mining event logs generated from PAIS for process model di
Externí odkaz:
http://arxiv.org/abs/1511.07023
Publikováno v:
Business Process Management Workshops: BPM 2015, 13th International Workshops, Innsbruck, Austria, August 31 - September 3, 2015, Revised Papers; 2016, p230-241, 12p
