arXiv subjects

Alessandro Bessi

Publications and source records attributed to Alessandro Bessi.

At least 19 recordsLinked to original sources

arXiv2021

Are renewable energies on a sustained path? Analysis of selected case-studies from the pre-pandemic-era

Provided widespread vaccination will bring the COVID-19 pandemic under full control worldwide, the contrast to climate change and the energy transition as one of its main actions will return at the top of national and international policy agendas. This paper employs multivariate diffusion models to investigate and quantitatively assess the competitive power of renewable energy technologies and their perspectives along the invoked energy transition. The study was conducted for the period 1965-2019 on a number of selected case studies, that were considered critically representative of the current transition process in view of their energy and political context. The dynamic relationship between renewable technologies and natural gas has been at the core of the analysis, trying to establish whether gas could be considered as a bridging technology or a lock-in. The main findings show that in all the analyzed countries RETs have exerted a strongly competitive effect towards gas. In most cases, gas is found to have a bridging role, aiding the uptake of renewables.

stat.AP↗

arXiv2018

Early Warnings of Cyber Threats in Online Discussions

We introduce a system for automatically generating warnings of imminent or current cyber-threats. Our system leverages the communication of malicious actors on the darkweb, as well as activity of cyber security experts on social media platforms like Twitter. In a time period between September, 2016 and January, 2017, our method generated 661 alerts of which about 84% were relevant to current or imminent cyber-threats. In the paper, we first illustrate the rationale and workflow of our system, then we measure its performance. Our analysis is enriched by two case studies: the first shows how the method could predict DDoS attacks, and how it would have allowed organizations to prepare for the Mirai attacks that caused widespread disruption in October 2016. Second, we discuss the method's timely identification of various instances of data breaches.

cs.CR↗

arXiv2017

Non-negative Tensor Factorization for Human Behavioral Pattern Mining in Online Games

Multiplayer online battle arena has become a popular game genre. It also received increasing attention from our research community because they provide a wealth of information about human interactions and behaviors. A major problem is extracting meaningful patterns of activity from this type of data, in a way that is also easy to interpret. Here, we propose to exploit tensor decomposition techniques, and in particular Non-negative Tensor Factorization, to discover hidden correlated behavioral patterns of play in a popular game: League of Legends. We first collect the entire gaming history of a group of about one thousand players, totaling roughly $100K$ matches. By applying our methodological framework, we then separate players into groups that exhibit similar features and playing strategies, as well as similar temporal trajectories, i.e., behavioral progressions over the course of their gaming history: this will allow us to investigate how players learn and improve their skills.

cs.LG↗

arXiv2016

Towards the Modeling of Behavioral Trajectories of Users in Online Social Media

In this paper, we introduce a methodology that allows to model behavioral trajectories of users in online social media. First, we illustrate how to leverage the probabilistic framework provided by Hidden Markov Models (HMMs) to represent users by embedding the temporal sequences of actions they performed online. We then derive a model-based distance between trained HMMs, and we use spectral clustering to find homogeneous clusters of users showing similar behavioral trajectories. To provide platform-agnostic results, we apply the proposed approach to two different online social media --- i.e. Facebook and YouTube. We conclude discussing merits and limitations of our approach as well as future and promising research directions.

cs.CY↗

arXiv2016

On the statistical properties of viral misinformation in online social media

The massive diffusion of online social media allows for the rapid and uncontrolled spreading of conspiracy theories, hoaxes, unsubstantiated claims, and false news. Such an impressive amount of misinformation can influence policy preferences and encourage behaviors strongly divergent from recommended practices. In this paper, we study the statistical properties of viral misinformation in online social media. By means of methods belonging to Extreme Value Theory, we show that the number of extremely viral posts over time follows a homogeneous Poisson process, and that the interarrival times between such posts are independent and identically distributed, following an exponential distribution. Moreover, we characterize the uncertainty around the rate parameter of the Poisson process through Bayesian methods. Finally, we are able to derive the predictive posterior probability distribution of the number of posts exceeding a certain threshold of shares over a finite interval of time.

cs.SI↗

arXiv2016

Echo Chambers: Emotional Contagion and Group Polarization on Facebook

Recent findings showed that users on Facebook tend to select information that adhere to their system of beliefs and to form polarized groups -- i.e., echo chambers. Such a tendency dominates information cascades and might affect public debates on social relevant issues. In this work we explore the structural evolution of communities of interest by accounting for users emotions and engagement. Focusing on the Facebook pages reporting on scientific and conspiracy content, we characterize the evolution of the size of the two communities by fitting daily resolution data with three growth models -- i.e. the Gompertz model, the Logistic model, and the Log-logistic model. Then, we explore the interplay between emotional state and engagement of users in the group dynamics. Our findings show that communities' emotional behavior is affected by the users' involvement inside the echo chamber. Indeed, to an higher involvement corresponds a more negative approach. Moreover, we observe that, on average, more active users show a faster shift towards the negativity than less active ones.

physics.soc-ph↗

arXiv2016

Personality Traits and Echo Chambers on Facebook

In online social networks, users tend to select information that adhere to their system of beliefs and to form polarized groups of like minded people. Polarization as well as its effects on online social interactions have been extensively investigated. Still, the relation between group formation and personality traits remains unclear. A better understanding of the cognitive and psychological determinants of online social dynamics might help to design more efficient communication strategies and to challenge the digital misinformation threat. In this work, we focus on users commenting posts published by US Facebook pages supporting scientific and conspiracy-like narratives, and we classify the personality traits of those users according to their online behavior. We show that different and conflicting communities are populated by users showing similar psychological profiles, and that the dominant personality model is the same in both scientific and conspiracy echo chambers. Moreover, we observe that the permanence within echo chambers slightly shapes users' psychological profiles. Our results suggest that the presence of specific personality traits in individuals lead to their considerable involvement in supporting narratives inside virtual echo chambers.

cs.SI↗

arXiv2016

Users Polarization on Facebook and Youtube

On social media algorithms for content promotion, accounting for users preferences, might limit the exposure to unsolicited contents. In this work, we study how the same contents (videos) are consumed on different platforms -- i.e. Facebook and YouTube -- over a sample of $12M$ of users. Our findings show that the same content lead to the formation of echo chambers, irrespective of the online social network and thus of the algorithm for content promotion. Finally, we show that the users' commenting patterns are accurate early predictors for the formation of echo-chambers.

cs.SI↗

arXiv2015

Debunking in a World of Tribes

Recently a simple military exercise on the Internet was perceived as the beginning of a new civil war in the US. Social media aggregate people around common interests eliciting a collective framing of narratives and worldviews. However, the wide availability of user-provided content and the direct path between producers and consumers of information often foster confusion about causations, encouraging mistrust, rumors, and even conspiracy thinking. In order to contrast such a trend attempts to \textit{debunk} are often undertaken. Here, we examine the effectiveness of debunking through a quantitative analysis of 54 million users over a time span of five years (Jan 2010, Dec 2014). In particular, we compare how users interact with proven (scientific) and unsubstantiated (conspiracy-like) information on Facebook in the US. Our findings confirm the existence of echo chambers where users interact primarily with either conspiracy-like or scientific pages. Both groups interact similarly with the information within their echo chamber. We examine 47,780 debunking posts and find that attempts at debunking are largely ineffective. For one, only a small fraction of usual consumers of unsubstantiated information interact with the posts. Furthermore, we show that those few are often the most committed conspiracy users and rather than internalizing debunking information, they often react to it negatively. Indeed, after interacting with debunking posts, users retain, or even increase, their engagement within the conspiracy echo chamber.

cs.CY↗

arXiv2015

Echo chambers in the age of misinformation

The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. Despite the enthusiastic rhetoric on the part of some that this process generates "collective intelligence", the WWW also allows the rapid dissemination of unsubstantiated conspiracy theories that often elicite rapid, large, but naive social responses such as the recent case of Jade Helm 15 -- where a simple military exercise turned out to be perceived as the beginning of the civil war in the US. We study how Facebook users consume information related to two different kinds of narrative: scientific and conspiracy news. We find that although consumers of scientific and conspiracy stories present similar consumption patterns with respect to content, the sizes of the spreading cascades differ. Homogeneity appears to be the primary driver for the diffusion of contents, but each echo chamber has its own cascade dynamics. To mimic these dynamics, we introduce a data-driven percolation model on signed networks.

cs.CY↗

arXiv2015

Emotional Dynamics in the Age of Misinformation

According to the World Economic Forum, the diffusion of unsubstantiated rumors on online social media is one of the main threats for our society. The disintermediated paradigm of content production and consumption on online social media might foster the formation of homophile communities (echo-chambers) around specific worldviews. Such a scenario has been shown to be a vivid environment for the diffusion of false claims, in particular with respect to conspiracy theories. Not rarely, viral phenomena trigger naive (and funny) social responses -- e.g., the recent case of Jade Helm 15 where a simple military exercise turned out to be perceived as the beginning of the civil war in the US. In this work, we address the emotional dynamics of collective debates around distinct kind of news -- i.e., science and conspiracy news -- and inside and across their respective polarized communities (science and conspiracy news). Our findings show that comments on conspiracy posts tend to be more negative than on science posts. However, the more the engagement of users, the more they tend to negative commenting (both on science and conspiracy). Finally, zooming in at the interaction among polarized communities, we find a general negative pattern. As the number of comments increases -- i.e., the discussion becomes longer -- the sentiment of the post is more and more negative.

cs.SI↗

arXiv2015

Trend of Narratives in the Age of Misinformation

Social media enabled a direct path from producer to consumer of contents changing the way users get informed, debate, and shape their worldviews. Such a {\em disintermediation} weakened consensus on social relevant issues in favor of rumors, mistrust, and fomented conspiracy thinking -- e.g., chem-trails inducing global warming, the link between vaccines and autism, or the New World Order conspiracy. In this work, we study through a thorough quantitative analysis how different conspiracy topics are consumed in the Italian Facebook. By means of a semi-automatic topic extraction strategy, we show that the most discussed contents semantically refer to four specific categories: {\em environment}, {\em diet}, {\em health}, and {\em geopolitics}. We find similar patterns by comparing users activity (likes and comments) on posts belonging to different semantic categories. However, if we focus on the lifetime -- i.e., the distance in time between the first and the last comment for each user -- we notice a remarkable difference within narratives -- e.g., users polarized on geopolitics are more persistent in commenting, whereas the less persistent are those focused on diet related topics. Finally, we model users mobility across various topics finding that the more a user is active, the more he is likely to join all topics. Once inside a conspiracy narrative users tend to embrace the overall corpus.

cs.SI↗

arXiv2015

Speeding up lower bound estimation in powerlaw distributions

The traditional lower bound estimation method for powerlaw distributions based on the Kolmogorov-Smirnov distance proved to perform better than other competing methods. However, if applied to very large collections of data, such a method can be computationally demanding. In this paper, we propose two alternative methods with the aim to reduce the time required by the estimation procedure. We apply the traditional method and the two proposed methods to large collections of data ($N = 500,000$) with varying values of the true lower bound. Both the proposed methods yield a significantly better performance and accuracy than the traditional method.

stat.CO↗

arXiv2015

Two samples test for discrete power-law distributions

Power-law distributions occur in wide variety of physical, biological, and social phenomena. In this paper, we propose a statistical hypothesis test based on the log-likelihood ratio to assess whether two samples of discrete data are drawn from the same power-law distribution.

stat.ME↗

arXiv2015

Structural Patterns of the Occupy Movement on Facebook

In this work we study a peculiar example of social organization on Facebook: the Occupy Movement -- i.e., an international protest movement against social and economic inequality organized online at a city level. We consider 179 US Facebook public pages during the time period between September 2011 and February 2013. The dataset includes 618K active users and 753K posts that received about 5.2M likes and 1.1M comments. By labeling user according to their interaction patterns on pages -- e.g., a user is considered to be polarized if she has at least the 95% of her likes on a specific page -- we find that activities are not locally coordinated by geographically close pages, but are driven by pages linked to major US cities that act as hubs within the various groups. Such a pattern is verified even by extracting the backbone structure -- i.e., filtering statistically relevant weight heterogeneities -- for both the pages-reshares and the pages-common users networks.

cs.SI↗

arXiv2015

Everyday the Same Picture: Popularity and Content Diversity

Facebook is flooded by diverse and heterogeneous content, from kittens up to music and news, passing through satirical and funny stories. Each piece of that corpus reflects the heterogeneity of the underlying social background. In the Italian Facebook we have found an interesting case: a page having more than $40K$ followers that every day posts the same picture of a popular Italian singer. In this work, we use such a page as a control to study and model the relationship between content heterogeneity on popularity. In particular, we use that page for a comparative analysis of information consumption patterns with respect to pages posting science and conspiracy news. In total, we analyze about $2M$ likes and $190K$ comments, made by approximately $340K$ and $65K$ users, respectively. We conclude the paper by introducing a model mimicking users selection preferences accounting for the heterogeneity of contents.

cs.SI↗

arXiv2014

Viral Misinformation: The Role of Homophily and Polarization

The spreading of unsubstantiated rumors on online social networks (OSN) either unintentionally or intentionally (e.g., for political reasons or even trolling) can have serious consequences such as in the recent case of rumors about Ebola causing disruption to health-care workers. Here we show that indicators aimed at quantifying information consumption patterns might provide important insights about the virality of false claims. In particular, we address the driving forces behind the popularity of contents by analyzing a sample of 1.2M Facebook Italian users consuming different (and opposite) types of information (science and conspiracy news). We show that users' engagement across different contents correlates with the number of friends having similar consumption patterns (homophily), indicating the area in the social network where certain types of contents are more likely to spread. Then, we test diffusion patterns on an external sample of $4,709$ intentional satirical false claims showing that neither the presence of hubs (structural properties) nor the most active users (influencers) are prevalent in viral phenomena. Instead, we found out that in an environment where misinformation is pervasive, users' aggregation around shared beliefs may make the usual exposure to conspiracy stories (polarization) a determinant for the virality of false information.

cs.SI↗

arXiv2014

Social determinants of content selection in the age of (mis)information

Despite the enthusiastic rhetoric about the so called \emph{collective intelligence}, conspiracy theories -- e.g. global warming induced by chemtrails or the link between vaccines and autism -- find on the Web a natural medium for their dissemination. Users preferentially consume information according to their system of beliefs and the strife within users of opposite narratives may result in heated debates. In this work we provide a genuine example of information consumption from a sample of 1.2 million of Facebook Italian users. We show by means of a thorough quantitative analysis that information supporting different worldviews -- i.e. scientific and conspiracist news -- are consumed in a comparable way by their respective users. Moreover, we measure the effect of the exposure to 4709 evidently false information (satirical version of conspiracy theses) and to 4502 debunking memes (information aiming at contrasting unsubstantiated rumors) of the most polarized users of conspiracy claims. We find that either contrasting or teasing consumers of conspiracy narratives increases their probability to interact again with unsubstantiated rumors.

cs.SI↗