Michael Soprano

Michael Soprano
University of Udine | UNIUD · Department of Economics and Statistics

Doctor of Philosophy
Postdoctoral Research Fellow at the University of Udine

About

22
Publications
1,061
Reads
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140
Citations
Citations since 2017
22 Research Items
140 Citations
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Introduction
I successfully defended my Ph.D. dissertation on May 22nd, 2023, and I plan to release it publicly soon (Computer Science, Mathematics And Physics course). My research interest centers around utilizing crowdsourcing-based approaches to address the ever-increasing problem of misinformation spread. As a long-term goal, I would like to leverage my skills in Computer Science to make a lasting contribution to the scientific community.
Education
November 2019 - January 2023
University of Udine
Field of study
  • Computer Science
March 2015 - March 2018
University of Udine
Field of study
  • Computer Science
September 2011 - March 2015
University of Udine
Field of study
  • Web and Multimedia Technologies

Publications

Publications (22)
Chapter
Full-text available
Conversational agents provide new modalities to access and interact with services and applications. Recently, they saw a backfire in their popularity, due to the recent advancements in language models. Such agents have been adopted in various fields such as healthcare and education, yet they received little attention in public administration. We de...
Chapter
Full-text available
In this paper, we present our journey in exploring the use of crowdsourcing for fact-checking. We discuss our early experiments aimed towards the identification of the best possible setting for misinformation assessment using crowdsourcing. Our results indicate that the crowd can effectively address misinformation at scale, showing some degree of c...
Conference Paper
Due to their relatively low cost and ability to scale, crowdsourcing based approaches are widely used to collect a large amount of human annotated data. To this aim, multiple crowdsourcing platforms exist, where requesters can upload tasks and workers can carry them out and obtain payment in return. Such platforms share a task design and deploy wor...
Article
Full-text available
Recent work has demonstrated the viability of using crowdsourcing as a tool for evaluating the truthfulness of public statements. Under certain conditions such as: (1) having a balanced set of workers with different backgrounds and cognitive abilities; (2) using an adequate set of mechanisms to control the quality of the collected data; and (3) usi...
Article
To scale the size of Information Retrieval collections, crowdsourcing has become a common way to collect relevance judgments at scale. Crowdsourcing experiments usually employ 100-10,000 workers, but such a number is often decided in a heuristic way. The downside is that the resulting dataset does not have any guarantee of meeting predefined statis...
Article
Automated fact-checking (AFC) systems exist to combat disinformation, however their complexity usually makes them opaque to the end user, making it difficult to foster trust in the system. In this paper, we introduce the E-BART model with the hope of making progress on this front. E-BART is able to provide a veracity prediction for a claim, and joi...
Article
Review scores collect users’ opinions in a simple and intuitive manner. However, review scores are also easily manipulable, hence they are often accompanied by explanations. A substantial amount of research has been devoted to ascertaining the quality of reviews, to identify the most useful and authentic scores through explanation analysis. In this...
Conference Paper
Due to the increasing amount of information shared online every day, the need for sound and reliable ways of distinguishing between trustworthy and non-trustworthy information is as present as ever. One technique for performing fact-checking at scale is to employ human intelligence in the form of crowd workers. Although earlier work has suggested t...
Article
Full-text available
Recently, the misinformation problem has been addressed with a crowdsourcing-based approach: to assess the truthfulness of a statement, instead of relying on a few experts, a crowd of non-expert is exploited. We study whether crowdsourcing is an effective and reliable method to assess truthfulness during a pandemic, targeting statements related to...
Preprint
Full-text available
Recent work has demonstrated the viability of using crowdsourcing as a tool for evaluating the truthfulness of public statements. Under certain conditions such as: (1) having a balanced set of workers with different backgrounds and cognitive abilities; (2) using an adequate set of mechanisms to control the quality of the collected data; and (3) usi...
Preprint
Full-text available
Recently, the misinformation problem has been addressed with a crowdsourcing-based approach: to assess the truthfulness of a statement, instead of relying on a few experts, a crowd of non-expert is exploited. We study whether crowdsourcing is an effective and reliable method to assess truthfulness during a pandemic, targeting statements related to...
Chapter
Review scores collect users’ opinions in a simple and intuitive manner. However, review scores are also easily manipulable, hence they are often accompanied by explanations. A substantial amount of research has been devoted to ascertaining the quality of reviews, to identify the most useful and authentic scores through explanation analysis. In this...
Conference Paper
Full-text available
Misinformation is an ever increasing problem that is difficult to solve for the research community and has a negative impact on the society at large. Very recently, the problem has been addressed with a crowdsourcing-based approach to scale up labeling efforts: to assess the truthfulness of a statement, instead of relying on a few experts, a crowd...
Preprint
Misinformation is an ever increasing problem that is difficult to solve for the research community and has a negative impact on the society at large. Very recently, the problem has been addressed with a crowdsourcing-based approach to scale up labeling efforts: to assess the truthfulness of a statement, instead of relying on a few experts, a crowd...
Preprint
Full-text available
Truthfulness judgments are a fundamental step in the process of fighting misinformation, as they are crucial to train and evaluate classifiers that automatically distinguish true and false statements. Usually such judgments are made by experts, like journalists for political statements or medical doctors for medical statements. In this paper, we fo...
Chapter
Full-text available
Information retrieval effectiveness evaluation is often carried out by means of test collections. Many works investigated possible sources of bias in such an approach. We propose a systematic approach to identify bias and its causes, and to remove it, thus enforcing fairness in effectiveness evaluation by means of test collections.
Chapter
Full-text available
Peer review is a well known mechanism exploited within the scholarly publishing process to ensure the quality of scientific literature. Such a mechanism, despite being well established and reasonable, is not free from problems, and alternative approaches to peer review have been developed. Such approaches exploit the readers of scientific publicati...
Chapter
Full-text available
This paper describes Readersourcing 2.0, an ecosystem providing an implementation of the Readersourcing approach proposed by Mizzaro [10]. Readersourcing is proposed as an alternative to the standard peer review activity that aims to exploit the otherwise lost opinions of readers. Readersourcing 2.0 implements two different models based on the so-c...
Conference Paper
Full-text available
We propose an alternative approach to the standard peer review activity that aims to exploit the otherwise lost opinions of readers of publications which is called Readersourcing, originally proposed by Mizzaro [ CITATION mizzaro-2012-readersourcing-a-manifesto \l 1040 ]. Such an approach can be formalized by means of different models which share t...
Article
Full-text available
Effectiveness evaluation of information retrieval systems by means of a test collection is a widely used methodology. However, it is rather expensive in terms of resources, time, and money; therefore, many researchers have proposed methods for a cheaper evaluation. One particular approach, on which we focus in this article, is to use fewer topics:...
Conference Paper
Full-text available
Several researchers have proposed to reduce the number of topics used in TREC-like initiatives. One research direction that has been pursued is what is the optimal topic subset of a given cardinality that evaluates the systems/runs in the most accurate way. Such a research direction has been so far mainly theoretical, with almost no indication on h...

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