Giancarlo Ruffo

• MD, PhD
• Professor (Associate) at Università del Piemonte Orientale "A. Avogadro"

Analyzing the financial domain presents significant challenges, particularly due to the lack of publicly available data and the limited opportunities for the scientific community to test methods and algorithms on real datasets. This paper explores the application of network analysis to the Anti-Financial Crime (AFC) domain, leveraging a large datas...

In recent years, the digitization and automation of anti-financial crime (AFC) investigative processes have faced significant challenges, particularly the need for interpretability of AI model results and the lack of labeled data for training. Network analysis has emerged as a valuable approach in this context. In this paper, we present WeirdFlows,...

We introduce EmoAtlas, a computational library/framework extracting emotions and syntactic/semantic word associations from texts. EmoAtlas combines interpretable artificial intelligence (AI) for syntactic parsing in 18 languages and psychologically validated lexicons for detecting the eight emotions in Plutchik’s theory. We show that EmoAtlas can m...

In the digital age, the challenge of forgetfulness has emerged as a significant concern, particularly regarding the management of personal data and its accessibility online. The right to be forgotten (RTBF) allows individuals to request the removal of outdated or harmful information from public access, yet implementing this right poses substantial...

We introduce EmoAtlas, a computational library/framework extracting emotions and syntactic/semantic word associations from texts. EmoAtlas combines interpretable artificial intelligence (AI) for syntactic parsing in 18 languages and psychologically-validated lexicons for detecting the 8 emotions in Plutchik's theory. We show that EmoAtlas can match...

Signed networks and balance theory provide a natural setting for real-world scenarios that show polarization dynamics, positive/negative relationships and political partisanship. For example, they have been proven effective in studying the increasing polarization of the votes in the two chambers of the U.S. Congress from World War II on Andris, Lee...

This work introduces EmoAtlas as a computational framework extracting emotions and syntactic/semantic word associations automatically from texts. EmoAtlas implements a cutting-edge synergy of interpretable artificial intelligence (AI) and psychologically-validated lexicons. Our framework supports out-of-the-box emotion detection of 8 categorical em...

We quantify social media user engagement with low-credibility online news media sources using a simple and intuitive methodology, that we showcase with an empirical case study of the Twitter debate on immigration in Italy. By assigning the Twitter users an Untrustworthiness ( U ) score based on how frequently they engage with unreliable media outle...

Misinformation posting and spreading in social media is ignited by personal decisions on the truthfulness of news that may cause wide and deep cascades at a large scale in a fraction of minutes. When individuals are exposed to information, they usually take a few seconds to decide if the content (or the source) is reliable and whether to share it....

Signed networks and balance theory provide a natural setting for real-world scenarios that show polarization dynamics, positive/negative relationships, and political partisanships. For example, they have been proven effective for studying the increasing polarization of the votes in the two chambers of the American Congress from World War II on. To...

COVID-19 vaccines have been largely debated by the press. To understand how mainstream and alternative media debated vaccines, we introduce a paradigm reconstructing time-evolving narrative frames via cognitive networks and natural language processing. We study Italian news articles massively re-shared on Facebook/Twitter (up to 5 million times), c...

In the last years, vaccines debate has attracted the attention of all the social media, with an outstanding increase during COVID-19 vaccination campaigns. The topic has created at least two opposing factions, pro- and anti-vaccines, that have conflicting and incompatible narratives. However, a not negligible fraction of the population has an uncle...

We propose a simple model of an idealized online cultural market in which $N$ items, endowed with a hidden quality metric, are recommended to users by a ranking algorithm possibly biased by the current items' popularity. Our goal is to better understand the underlying mechanisms of the well-known fact that popularity bias can prevent higher-quality...

We propose a simple model of an idealized online cultural market in which N items, endowed with a hidden quality metric, are recommended to users by a ranking algorithm possibly biased by the current items’ popularity. Our goal is to better understand the underlying mechanisms of the well-known fact that popularity bias can prevent higher-quality i...

We present three models used to describe the recruitment of the undecided population by pro-vax and no-vax factions. Starting from real-world data of Facebook pages, we compare three opinion dynamics models that catch different behaviours of the undecided population. The first one is a variation of the SIS model, where undecided position is conside...

Since their announcement in November 2020, COVID-19 vaccines were largely debated by the press and social media. With most studies focusing on COVID-19 disinformation in social media, little attention has been paid to how mainstream news outlets framed COVID-19 narratives compared to alternative sources. To fill this gap, we use cognitive network s...

We studied international migrations of researchers, scientists, and academics, to better understand the so-called “brain drain” phenomenon, if and how it can be measured, and how it changes over time. We discuss why some trivial measures can be ineffective, and as a consequence, we built the global scientific migration network to identify the most...

Misinformation posting and spreading in Social Media is ignited by personal decisions on the truthfulness of news that may cause wide and deep cascades at a large scale in a fraction of minutes. When individuals are exposed to information, they usually take a few seconds to decide if the content (or the source) is reliable, and eventually to share...

The history of journalism and news diffusion is tightly coupled with the effort to dispel hoaxes, misinformation, propaganda, unverified rumours, poor reporting, and messages containing hate and divisions. With the explosive growth of online social media and billions of individuals engaged with consuming, creating, and sharing news, this ancient pr...

The increasing availability of textual corpora and data fetched from social networks is fuelling a huge production of works based on the model proposed by psychologist Robert Plutchik, often referred simply as the “Plutchik Wheel”. Related researches range from annotation tasks description to emotions detection tools. Visualisation of such emotions...

In this work we study how pervasive is the presence of disinformation in the Italian debate around immigration on Twitter and the role of automated accounts in the diffusion of such content. By characterising the Twitter users with an \textit{Untrustworthiness} score, that tells us how frequently they engage with disinformation content, we are able...

In this paper we propose a data acquisition methodology, and a Machine Learning solution for the partially automated evaluation of real estate properties. The novelty and importance of the approach lies in two aspects: (1) when compared to Automated Valuation Models (AVMs) as available to real estate operators, it is highly adaptive and non-paramet...

The increasing availability of textual corpora and data fetched from social networks is fuelling a huge production of works based on the model proposed by psychologist Robert Plutchik, often referred simply as the ``Plutchik Wheel''. Related researches range from annotation tasks description to emotions detection tools. Visualisation of such emotio...

Abstract The always increasing mobile connectivity affects every aspect of our daily lives, including how and when we keep ourselves informed and consult news media. By studying a DPI (deep packet inspection) dataset, provided by one of the major Chilean telecommunication companies, we investigate how different cohorts of the population of Santiago...

In this work, we apply network science to analyse almost 6 M tweets about the debate around immigration in Italy, collected between 2018 and 2019, when many related events captured media outlets’ attention. Our aim was to better understand the dynamics underlying the interactions on social media on such a delicate and divisive topic, which are the...

We aim to explore the connections between structural network inequalities and bank’s customer spending behaviours, within an entire national ecosystem made of natural persons (i.e., an individual human being) and legal entities (i.e., private or public organisations), different business sectors, and supply chains that span distinct geographical reg...

Interest has grown around the classification of stance that users assume within online debates in recent years. Stance has been usually addressed by considering users posts in isolation, while social studies highlight that social communities may contribute to influence users' opinion. Furthermore, stance should be studied in a diachronic perspectiv...

Interest has grown around the classification of stance that users assume within online debates in recent years. Stance has been usually addressed by considering users posts in isolation, while social studies highlight that social communities may contribute to influence users' opinion. Furthermore, stance should be studied in a diachronic perspectiv...

The paper describes the Web platform built within the project “Contro l’Odio”, for monitoring and contrasting discrimination and hate speech against immigrants in Italy. It applies a combination of computational linguistics techniques for hate speech detection and data visualization tools on data drawn from Twitter.It allows users to access a huge...

Network visualization has established as a key complement to network analysis since the large variety of existing network layouts are able to graphically highlight different properties of networks. However, signed networks, i.e., networks whose edges are labeled as friendly (positive) or antagonistic (negative), are target of few of such layouts an...

Abstract We propose a framework to study the spreading of urban legends, i.e., false stories that become persistent in a local popular culture, where social groups are naturally segregated by virtue of many (both mutable and immutable) attributes. The goal of this work is identifying and testing new strategies to restrain the dissemination of false...

Network visualization has established as a key complement to network analysis since the large variety of existing network layouts are able to graphically highlight different properties of networks. However, signed networks, i.e., networks whose edges are labeled as friendly (positive) or antagonistic (negative), are target of few of such layouts an...

The paper describes the Web platform built within the project "Contro l'odio", for monitoring and contrasting discrimination and hate speech against immigrants in Italy. It applies a combination of computational linguistics techniques for hate speech detection and data visualization tools on data drawn from Twitter. It allows users to access a huge...

Signed networks contain edge annotations to indicate whether each interaction is friendly (positive edge) or antagonistic (negative edge). The model is simple but powerful and it can capture novel and interesting structural properties of real-world phenomena. The analysis of signed networks has many applications from modeling discussions in social...

Signed networks contain edge annotations to indicate whether each interaction is friendly (positive edge) or antagonistic (negative edge). The model is simple but powerful and it can capture novel and interesting structural properties of real-world phenomena. The analysis of signed networks has many applications from modeling discussions in social...

Real estate appraisal is a complex and important task, that can be made more precise and faster with the help of automated valuation tools. Usually the value of some property is determined by taking into account both structural and geographical characteristics. However, while geographical information is easily found, obtaining significant structura...

In the last decade, social media gained a very significant role in public debates, and despite the many intrinsic difficulties of analyzing data streaming from on-line platforms that are poisoned by bots, trolls, and low-quality information, it is undeniable that such data can still be used to test the public opinion and overall mood and to investi...

In this work we study international migrations of researchers, scientists, and academics from a complex-network perspective to identify the central countries involved in the migration phenomenon. We define the scientific migration network (SMN) as temporal directed weighted network where nodes are world countries, links account for the number of sc...

The always increasing mobile connectivity affects every aspect of our daily lives, including how and when we keep ourselves informed and consult news media. By studying mobile web data, provided by one of the major Chilean telecommunication companies, we investigate how different cohorts of the population of Santiago De Chile consume news media con...

In this paper we present a data visualization platform designed to support the Natural Language Processing (NLP) scholar to study and analyze different corpora collected with the purpose to understand the hate speech phenomenon in social media. The project started with the creation of a corpus which collects tweets addressed to specific groups of e...

Misinformation under the form of rumor, hoaxes, and conspiracy theories spreads on social media at alarming rates. One hypothesis is that, since social media are shaped by homophily, belief in misinformation may be more likely to thrive on those social circles that are segregated from the rest of the network. One possible antidote is fact checking...

The number of communications and messages generated by users on social media platforms has progressively increased in the last years. Therefore, the issue of developing automated systems for a deep analysis of users' generated contents and interactions is becoming increasingly relevant. In particular, when we focus on the domain of online political...

Thanks to the advancements in ubiquitous and wearable technologies, Personal Informatics (PI) systems can now reach a larger audience of users. However, it is not still clear whether this kind of tool can fit the needs of their daily lives. Our research aims at identifying specific barriers that may prevent the widespread adoption of PI and finding...

This paper focuses on the role of social relations within social media in the formation of public opinion. We propose to combine the detection of the users' stance towards BREXIT, carried out by content analysis of Twitter messages, and the exploration of their social relations, by relying on social network analysis. The analysis of a novel Twitte...

Misinformation under the form of rumor, hoaxes, and conspiracy theories spreads on social media at alarming rates. One hypothesis is that, since social media are shaped by homophily, belief in misinformation may be more likely to thrive on those social circles that are segregated from the rest of the network. One possible antidote is fact checking...

The use of irony and sarcasm has been proven to be a pervasive phenomenon in social media posing a challenge to sentiment analysis systems. Such devices, in fact, can influence and twist the polarity of an utterance in different ways. A new dataset of over 10,000 tweets including a high variety of figurative language types, manually annotated with...

The goal of this work is to introduce a simple modeling framework to study the diffusion of hoaxes and in particular how the availability of debunking information may contain their diffusion. As traditionally done in the mathematical modeling of information diffusion processes, we regard hoaxes as viruses: users can become infected if they are expo...

Nowadays, smartphones and digital networks are being heavily used as data sources for research on social networks. Our daily experiences, interactions and transactions are recorded thanks to the digital traces that users leave behind their activities, both individual and social. In this work, we describe AiRCacher, a mobile app for virtual geocachi...

Bots are, for many Web and social media users, the source of many dangerous attacks or the carrier of unwanted messages, such as spam. Nevertheless, crawlers and software agents are a precious tool for analysts, and they are continuously executed to collect data or to test distributed applications. However, no one knows which is the real potential...

In this chapter, the authors discuss the state-of-the-art of Geo-Social systems and Recommender systems, which are becoming extremely popular for users accessing social media trough mobile devices. Moreover, they introduce a general framework based on the interaction among those systems and the "Game With A Purpose" (GWAP) paradigm. The proposed fr...

Felicittà1 is an online platform for estimating happiness in the Italian cities, which uses Twitter as data source and combines sentiment analysis and visualization techniques in order to provide users with an interactive interface for data exploration. In particular, Felicittà daily analyzes Twitter posts and exploits temporal and geo-spatial info...

Complex dynamics of social media emerge from the interaction between the patterns of social connectivity of users and the information exchanged along such social ties. Unveiling the underlying mechanisms that drive the evolution of online social systems requires a deep understanding of the interplay between these two aspects. Based on the case of t...

We report on a data-driven investigation aimed at understanding the dynamics of message spreading in a real-world dynamical network of human proximity. We use data collected by means of a proximity-sensing network of wearable sensors that we deployed at three different social gatherings, simultaneously involving several hundred individuals. We simu...

The evolution of the role of online social networks in the Web has led to a collision between private, public and commercial spheres that have been inevitably connected together in social networking services since their beginning. The growing awareness on the opaque data management operated by many providers reveals that a privacy-aware service tha...

Structured overlay networks are highly susceptible to attacks aimed at subverting their structure or functionalities. Although many secure architectural design proposals have been presented in the past, a widely accepted and comprehensive solution is lacking. Likir (Layered Identity-based Kademlia-like Infrastructure) is our solution for implementi...

Social search is having a flourishing success for its effectiveness in retrieving high quality information useful to achieve complex search goals. Surprisingly, the potential of the social paradigm at the basis of collaborative tagging in satisfying complex search intents has been unexplored so far. We propose an extended model of folksonomies that...

This paper introduces the SALC project which aims at developing a technological , extensible platform enabling on demand aggregate of heterogeneous digital media services. It experiments emerging MPEG technologies in the field of audiovisual content management on distributed networks that can benefit broadcasters as well as multimedia archive stake...

In order to integrate properly recording services with other streaming functionalities in a DMR (e.g., AppleTV, PS3) we need a way to put live TV and radio events into friendly catalogs. But recordings are based on parameters to be set by the users, such as timings and channels, and event discovery can be not trivial. Moreover, personalized recomme...

Recommendation is usually reduced to a prediction problem over the function $r(u_a, e_i)$ that returns the expected rating of element $e_i$ for user $u_a$. In the IPTV domain, we deal with an environment where the definitions of all the parameters involved in this function (i.e., user profiles, feedback ratings and elements) are controversial. To o...

The chapter deals with the social impact of P2P systems in light of a bidirectional connection by which technological developments influence, in a complex and often unpredictable way, the social environment whereas the dynamic evolution of the latter does affect technological progress. From this perspective, the aim is to deepen legal issues, socio...

The present work investigates the structural and dynamical properties of aNobii, a social bookmarking system designed for readers and book lovers. Users of aNobii provide information about their library, reading interests and geographical location, and they can establish typed social links to other users. Here, we perform an in-depth analysis of th...

The present work investigates the structural and dynamical properties of aNobii\footnote{http://www.anobii.com/}, a social bookmarking system designed for readers and book lovers. Users of aNobii provide information about their library, reading interests and geographical location, and they can establish typed social links to other users. Here, we p...

We introduce collaborative tagging and faceted search on structured P2P systems. Since a trivial and brute force mapping of an entire folksonomy over a DHT-based system may reduce scalability, we propose an approximated graph maintenance approach. Evaluations on real data coming from Last.fm prove that such strategies reduce vocabulary noise (i.e.,...

The rapid growth of the volume of user-generated contents in online social networks has raised many privacy concerns, mainly due to the data exploitation operated by providers. In order to address this problem, the idea of supporting social network services with open peer-to-peer systems has gained ground very recently. Nevertheless, the developmen...

Providing valuable recommendations in the DVR domain is quite straightforward when enough information about users and/or contents is known. In this work, we discuss the pos-sibility of recommending future live events without knowing anything else but past user programmed recording sched-ules.

In this paper we investigate the topology of the in ter-firm labor mobility network in a leading Italian region. Using a unique matched employer-employee dataset that covers the entire private sector throughout the 90s, we construct a directed network in which the firms represent the vertices and the transitions of worker from firm to firm for m th...

Recommendation Systems can be one of the killer applica-tions for a new generation of PVRs. Unfortunately, these systems do not apply directly to this domain because of the unreliability of EPGs and registrations set on temporal basis instead of discrete objects. We propose a method for dis-cretizing temporal and volatile events and the preliminary...

Network analysis has proved to be very useful in many social and natural sciences, and in particular Small World topologies have been exploited in many application fields. In this article, we focus on P2P file sharing applications, where spontaneous communities of users are studied and analyzed. We define a family of structures that we call “Affini...

A multimedia communication system enables multimedia data's generation, storage, management, distribution, receiving, consuming, editing, sharing, and so on. In such systems, there are various security issues, which must be considered such as eavesdropping, intrusion, forgery, piracy and privacy, etc. Until now, various security solutions for multi...

We focus on collaborative filtering dealing with self-organizing communities, host mobility, wireless access, and ad-hoc communications. In such a domain, knowledge representation and users profiling can be hard; remote servers can be often unreachable due to client mobility; and feedback ratings collected during random connections to other users'...

The lack of a trusted authority, responsible for peers' identity verification or for authentication purposes, makes actual P2P systems extremely vulnerable to a large spectrum of attacks. The main purpose of this paper is to present Likir (Layered Identity-based Kademlia-like InfRastructure), a framework that includes an identity-based scheme and a...

The city of Torino, Italy, is to host for the first time the ACM Hypertext and Hypermedia Conference in 2009. Hypertext 2009, sponsored by ACM and SIGWEB, will be held from June 29th to July 1st at the Villa Gualino Convention Centre (www.villagualino.net), on the hills overlooking Torino. Professionals from academia, industry and the media will pr...

Both web services framework and peer-to-peer networks provide a discovery process, but as current P2P systems focus more on the discovery of content in the form of com-mon files (possibly associated with metadata), a centralized UDDI registry serves content in the form of metadata de-scribing web services. Thus, the intersection between P2P and Web...

The technical impact of the Peer-to-Peer (P2P) paradigm on content distribution applications has been proved successful and efficient, when participants cooperation is achieved. Conversely, the business model is not clear: given a copy-protected object, its owner must be paid back for each transaction taking place from a provider to a receiver. The...

As the nodes and the resources in a structured peer-to-peer network are indexed with unique identifiers, and as the identifiers are assigned to nodes whose nodeId (i.e., the identifier of the peer) is closest (by some metrics) to the identifier, at an application level it is an issue to know the unique identifier a resource is indexed with, to rout...

The "small world"-paradigm offers a new interesting view-point for the analysis of contemporary legal networks and artificial intelligence. This topological approach sheds further light on such different fields as case-based legal reasoning, knowledge discovery in legal databases, or legal ontologies, as far as clustering coefficients, diameter and...

The validation of a recommender system is always a quite hazardous task, because of the diculty of modeling the tastes of a given user. Novel (decentralized) recommender systems are proposed and evaluated by way of well known logs of user profiles and buddy tables, that contain lists of items with feedback ratings assigned by a given set of users....

Recently, Steve Jobs, in his public “Thoughts on Music”, pointed out the Digital Rights Management (DRM) systems that Apple has been imposed to adopt for protecting its music against piracy. This brings to a paradox: DRM-protected digital music is prevented from being played by devices of different producers. Conversely, DRM-free content, that uses...

Small World patterns have been found in many social and natural networks, and even in Peer-to-Peer topologies. In this paper, we analyze File Sharing applications that aggregate virtual communities of users exchanging data. In these domains, it is possible to define overlaying structures that we call “Preference Networks” that show self organized i...

Structured peer-to-peer overlay network is an efficient solution for querying and retrieving resources spread between the peers. Unfortunately, key based routing of Distributed Hash Tables is simple when keys are known in advance, and at the service level this connot be always assumed. In this paper1, we present DHTeach, an e-learning application b...

In this paper we present a time sensitive content distribution system under implementation with the following innovative features: (a) events can be accessed and distributed using a fully decentralized DHT-based platform, (b) the bootstrap problem is solved by means of a permanent core network made of always alive nodes, (c) the streams are served...

A peer-to-peer market place is likely to be based on some underlying micro-payment scheme where each user can act both as a customer and as a merchant. Such systems, even when designed for largely distributed domains, may be implemented according to hybrid topologies where trusted third intermediaries (e.g. the broker) are single points of failures...

In this paper we show experimentally that typing dynamics of free text provide useful information for user identification and authentication even when a long time has passed since typing profiles of users were formed, and even when users are writing in a language different from the one used to form their profiles. Hence, we argue that keystroke ana...