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Michael Soprano
Michael Soprano
Postdoctoral Research Fellow at the University of Udine
Verified email at uniud.it - Homepage
Title
Cited by
Cited by
Year
Can the crowd identify misinformation objectively? The effects of judgment scale and assessor's background
K Roitero, M Soprano, S Fan, D Spina, S Mizzaro, G Demartini
Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020
672020
The many dimensions of truthfulness: Crowdsourcing misinformation assessments on a multidimensional scale
M Soprano, K Roitero, D La Barbera, D Ceolin, D Spina, S Mizzaro, ...
Information Processing & Management 58 (6), 102710, 2021
542021
The covid-19 infodemic: Can the crowd judge recent misinformation objectively?
K Roitero, M Soprano, B Portelli, D Spina, V Della Mea, G Serra, ...
Proceedings of the 29th ACM international conference on information …, 2020
532020
Can the crowd judge truthfulness? A longitudinal study on recent misinformation about COVID-19
K Roitero, M Soprano, B Portelli, M De Luise, D Spina, VD Mea, G Serra, ...
Personal and Ubiquitous Computing, 1-31, 2023
302023
The effects of crowd worker biases in fact-checking tasks
T Draws, D La Barbera, M Soprano, K Roitero, D Ceolin, A Checco, ...
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
292022
Crowd_Frame: a simple and complete framework to deploy complex crowdsourcing tasks off-the-shelf
M Soprano, K Roitero, F Bombassei De Bona, S Mizzaro
Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022
112022
E-bart: Jointly predicting and explaining truthfulness
E Brand, K Roitero, M Soprano, G Demartini
Proceedings of the Conference for Truth and Trust Online, 2021
102021
Cognitive Biases in Fact-Checking and Their Countermeasures: A Review
M Soprano, K Roitero, D La Barbera, D Ceolin, D Spina, G Demartini, ...
Information Processing & Management 61 (3), 103672, 2024
82024
A neural model to jointly predict and explain truthfulness of statements
E Brand, K Roitero, M Soprano, A Rahimi, G Demartini
ACM Journal of Data and Information Quality 15 (1), 1-19, 2022
82022
Transparent assessment of information quality of online reviews using formal argumentation theory
D Ceolin, G Primiero, M Soprano, J Wielemaker
Information Systems 110, 102107, 2022
82022
Assessing the Quality of Online Reviews Using Formal Argumentation Theory
D Ceolin, G Primiero, J Wielemaker, M Soprano
72021
Reproduce and Improve: An Evolutionary Approach to Select a Few Good Topics for Information Retrieval Evaluation
K Roitero, M Soprano, A Brunello, S Mizzaro
Journal of Data and Information Quality (JDIQ) 10 (3), 1-21, 2018
72018
Crowdsourcing Peer Review: As We May Do
M Soprano, S Mizzaro
Italian Research Conference on Digital Libraries, 259-273, 2019
52019
Effectiveness evaluation with a subset of topics: A practical approach
K Roitero, M Soprano, S Mizzaro
The 41st International ACM SIGIR Conference on Research & Development in …, 2018
42018
How many crowd workers do I need? On statistical power when crowdsourcing relevance judgments
K Roitero, DL Barbera, M Soprano, G Demartini, S Mizzaro, T Sakai
ACM Transactions on Information Systems 42 (1), 1-26, 2023
32023
Towards a conversational-based agent for health services
M Soprano, K Roitero, V Della Mea, S Mizzaro
Proceedings of the Italia Intelligenza Artificiale-Thematic Workshops co …, 2023
22023
Fact-checking at scale with crowdsourcing: Experiments and lessons learned
D La Barbera, M Soprano, K Roitero, E Maddalena, S Mizzaro
Proceedings of the 13th Italian Information Retrieval Workshop 3448, 85-90, 2023
12023
HITS Hits Readersourcing: Validating Peer Review Alternatives Using Network Analysis.
M Soprano, K Roitero, S Mizzaro
BIRNDL@ SIGIR, 70-82, 2019
12019
Bias and fairness in effectiveness evaluation by means of network analysis and mixture models
M Soprano, K Roitero, S Mizzaro
CEUR Workshop Proceedings 2441, 6-7, 2019
12019
Crowdsourced Fact-checking: Does It Actually Work?
D La Barbera, E Maddalena, M Soprano, K Roitero, G Demartini, D Ceolin, ...
Information Processing & Management 61 (5), 103792, 2024
2024
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