Nathan Bartley
University of Southern California
8 Papers
234 Citations
Nathan Bartley is an academic researcher from University of Southern California. The author has contributed to research in topics: Computer science & Social media. The author has an hindex of 5, co-authored 7 publications. Previous affiliations of Nathan Bartley include University of Chicago & Information Sciences Institute.
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Papers
Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science
Randal S. Olson,Nathan Bartley,Ryan J. Urbanowicz,Jason H. Moore +3 more
- 20 Jul 2016
TL;DR: TPOT as mentioned in this paper is an open source Tree-based Pipeline Optimization Tool (TPOT) in Python that can design machine learning pipelines that provide a significant improvement over a basic machine learning analysis while requiring little to no input nor prior knowledge from the user.
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Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science
TL;DR: This paper implements an open source Tree-based Pipeline Optimization Tool (TPOT) in Python and shows that TPOT can design machine learning pipelines that provide a significant improvement over a basic machine learning analysis while requiring little to no input nor prior knowledge from the user.
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Auditing Algorithmic Bias on Twitter
Nathan Bartley,Andrés Abeliuk,Emilio Ferrara,Kristina Lerman +3 more
- 21 Jun 2021
TL;DR: In this paper, the authors implement a sock-puppet audit, a computational framework to audit black-box social media systems so as to quantify the impact of algorithmic curation on the information people see.
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Discovering Signals from Web Sources to Predict Cyber Attacks.
Palash Goyal,K. S. M. Tozammel Hossain,Ashok Deb,Nazgol Tavabi,Nathan Bartley,Andrés Abeliuk,Emilio Ferrara,Kristina Lerman +7 more
TL;DR: Performance of the framework across ground truth data over real-world forecasting tasks shows that the methods yield a significant lift or increase of F1 for the top signals on predicted cyber attacks.
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Understanding Cyberbullying on Instagram and Ask.fm via Social Role Detection
Hsien-Te Kao,Shen Yan,Di Huang,Nathan Bartley,Homa Hosseinmardi,Emilio Ferrara +5 more
- 13 May 2019
TL;DR: This work proposes a social role detection framework to understand cyberbullying on online social platforms, and selects a dataset that contains users’ records on both Instagram and Ask.fm as a case study.
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