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ORCID8th HCOMP 2020: Hilversum, The Netherlands [virtual]
- Lora Aroyo, Elena Simperl:
Proceedings of the Eighth AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2020, Hilversum, The Netherlands (virtual), October 25-29, 2020. AAAI Press 2020, ISBN 978-1-57735-848-0
Full Papers
- Tahir Abbas
, Vassilis-Javed Khan, Ujwal Gadiraju, Panos Markopoulos:
Trainbot: A Conversational Interface to Train Crowd Workers for Delivering On-Demand Therapy. 3-12 - Abdullah B. Alshaibani, Sylvia T. Carrell, Li-Hsin Tseng, Jungmin Shin, Alexander J. Quinn:
Privacy-Preserving Face Redaction Using Crowdsourcing. 13-22 - Yukino Baba, Jiyi Li, Hisashi Kashima:
CrowDEA: Multi-View Idea Prioritization with Crowds. 23-32 - Anubrata Das, Brandon Dang, Matthew Lease:
Fast, Accurate, and Healthier: Interactive Blurring Helps Moderators Reduce Exposure to Harmful Content. 33-42 - Alexander Erlei, Franck Awounang Nekdem, Lukas Meub, Avishek Anand, Ujwal Gadiraju:
Impact of Algorithmic Decision Making on Human Behavior: Evidence from Ultimatum Bargaining. 43-52 - Danula Hettiachchi, Senuri Wijenayake, Simo Hosio, Vassilis Kostakos, Jorge Gonçalves:
How Context Influences Cross-Device Task Acceptance in Crowd Work. 53-62 - Donald R. Honeycutt, Mahsan Nourani, Eric D. Ragan:
Soliciting Human-in-the-Loop User Feedback for Interactive Machine Learning Reduces User Trust and Impressions of Model Accuracy. 63-72 - Ryan Kemmer, Yeawon Yoo, Adolfo R. Escobedo, Ross Maciejewski:
Enhancing Collective Estimates by Aggregating Cardinal and Ordinal Inputs. 73-82 - Qing Li, Sharon Lynn Chu, Nanjie Rao, Mahsan Nourani:
Understanding the Effects of Explanation Types and User Motivations on Recommender System Use. 83-91 - Nir Machlev, David Sarne:
Predicting Crowdworkers' Performance as Human-Sensors for Robot Navigation. 92-101 - Ido Nimni, David Sarne:
Effective Operator Summaries Extraction. 102-111 - Mahsan Nourani, Joanie T. King, Eric D. Ragan:
The Role of Domain Expertise in User Trust and the Impact of First Impressions with Intelligent Systems. 112-121 - Amy Rechkemmer, Ming Yin:
Motivating Novice Crowd Workers through Goal Setting: An Investigation into the Effects on Complex Crowdsourcing Task Training. 122-131 - Marta Sabou, Klemens Käsznar, Markus Zlabinger, Stefan Biffl, Dietmar Winkler:
Verifying Extended Entity Relationship Diagrams with Open Tasks. 132-140 - Gerard van Alphen, Sihang Qiu, Alessandro Bozzon, Geert-Jan Houben:
Analyzing Workers Performance in Online Mapping Tasks Across Web, Mobile, and Virtual Reality Platforms. 141-149
Short Papers
- Sohail Akhtar, Valerio Basile, Viviana Patti:
Modeling Annotator Perspective and Polarized Opinions to Improve Hate Speech Detection. 151-154 - Xiaoni Duan, Chien-Ju Ho, Ming Yin:
Does Exposure to Diverse Perspectives Mitigate Biases in Crowdwork? An Explorative Study. 155-158 - Claudia Flores-Saviaga, Yuwen Li, Benjamin V. Hanrahan, Jeffrey P. Bigham, Saiph Savage:
The Challenges of Crowd Workers in Rural and Urban America. 159-162 - Masanari Kimura, Kei Wakabayashi, Atsuyuki Morishima:
Batch Prioritization of Data Labeling Tasks for Training Classifiers. 163-167 - Hua Shen, Ting-Hao (Kenneth) Huang:
How Useful Are the Machine-Generated Interpretations to General Users? A Human Evaluation on Guessing the Incorrectly Predicted Labels. 168-172 - Alexandra Uma, Tommaso Fornaciari, Dirk Hovy, Silviu Paun, Barbara Plank, Massimo Poesio:
A Case for Soft Loss Functions. 173-177 - Xiaotong (Tone) Xu, Judith E. Fan, Steven P. Dow:
Schema and Metadata Guide the Collective Generation of Relevant and Diverse Work. 178-182
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