Darren Gergle

Sociology and Political Science · 2002–2018

A researcher in the Science corpus: 9 papers; trusts 22 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Sociology and Political Science — 26 citations into it; #5,896 of 22,756 by trust here, #9,515 by citations
• Artificial Intelligence — 25 citations into it; #34,778 of 35,345 by trust here, #19,439 by citations
• Information Systems — 23 citations into it; #2,710 of 8,771 by trust here, #3,761 by citations
• Human-Computer Interaction — 20 citations into it
• Computer Science Applications — 15 citations into it; #1,667 of 1,855 by trust here, #1,224 by citations
• Computer Vision and Pattern Recognition — 12 citations into it
• Natural Language Processing — 10 citations into it; #5,586 of 5,688 by trust here, #3,574 by citations
• Safety Research — 10 citations into it; #5,282 of 5,829 by trust here, #4,390 by citations

Whom Darren Gergle trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Andrew F. Hayes
2. Scott A. Shane
3. K. Seers
4. James Hays
5. Yan Zhang
6. Sonja Utz
7. K. Kroenke
8. David J. Crandall
9. Nitesh V. Chawla
10. Jacob O. Wobbrock

Who trusts Darren Gergle overall

1. Isaac L. Johnson
2. Brent J. Hecht
3. Johannes Schöning

Papers from Darren Gergle's perspective

Ordered by how strongly the researchers Darren Gergle trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. GloVe: Global Vectors for Word Representation
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Unbiased look at dataset bias
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Addressing Age-Related Bias in Sentiment Analysis (2018) — 227 citations
• Effects of four computer-mediated communications channels on trust development (2002) — 488 citations
• "Algorithms ruin everything": #RIPTwitter, Folk Theories, and Resistance to Algorithmic Change in Social Media (2017) — 308 citations
• On the "localness" of user-generated content (2010) — 331 citations
• IntroAssist: A Tool to Support Writing Introductory Help Requests (2018) — 70 citations
• It's (Not) Simply a Matter of Time: The Relationship Between CMC Cues and Interpersonal Affinity (2016) — 37 citations
• To search or to ask: the routing of information needs between traditional search engines and social networks (2014) — 72 citations
• Harnessing Context Sensing to Develop a Mobile Intervention for Depression (2011) — 618 citations
• The aligned rank transform for nonparametric factorial analyses using only anova procedures (2011) — 2,979 citations