A5014698350- Misinformation and Its Impacts
- Media Influence and Politics
- Social Media and Politics
- Opinion Dynamics and Social Influence
- Vaccine Coverage and Hesitancy
- Complex Systems and Time Series Analysis
- Complex Network Analysis Techniques
- Financial Risk and Volatility Modeling
- Statistical Methods and Bayesian Inference
- Hate Speech and Cyberbullying Detection
- Stock Market Forecasting Methods
- Time Series Analysis and Forecasting
- Advanced Statistical Methods and Models
- Odor and Emission Control Technologies
- Indoor Air Quality and Microbial Exposure
- Mathematical Dynamics and Fractals
- Air Quality and Health Impacts
- Media Studies and Communication
- Statistical Methods and Inference
- 3D Modeling in Geospatial Applications
- Public Relations and Crisis Communication
- Financial Markets and Investment Strategies
- Topic Modeling
- Spam and Phishing Detection
Ca' Foscari University of Venice
2018-2024
Introduction. Formaldehyde, a colorless and highly irritating substance, causes cancer of the nasopharynx leukemia. Furthermore, it is one environmental mutagens to which humans are most abundantly exposed. Acetaldehyde was recently classified as carcinogen class 1B mutagen 2 in Annex VI EC regulation. Occupational exposure two aldehydes occurs wide variety occupations industries. The aim this study deepen non-traditional productive sectors bakeries pastry producers. Methods. evaluation...
The claim of Cambridge Analytica, a political consulting firm, that it was possible to influence voting behavior by using data mined from the social platform Facebook created sudden fear in its users being manipulated; consequently, even market price shocked.We propose case study analyzing effect this scandal not only on stock price, but also whole market. To such scope, we consider 15-minutes prices and returns set NASDAQ-100 components before after Analytica case. We analyze correlations...
The COVID-19 pandemic made explicit the issues of communicating science in an information ecosystem dominated by social media platforms. One fundamental communication challenges our time is to provide public with reliable content and contrast misinformation. This paper investigates how can become effective channel promote engagement (re)build trust. To measure response quality communication, we conducted experimental study test a set recommendations on Facebook Twitter. experiment involved...
Recognizing the presence and impact of news outlets' biases on public discourse is a crucial challenge. Biased significantly shapes how individuals perceive events, potentially jeopardizing individual wellbeing. In assessing outlet reliability, focus has predominantly centered narrative bias, sidelining other such as selecting events favoring specific perspectives (selection bias). Leveraging machine learning techniques, we have compiled six-year dataset articles related to vaccines,...
Abstract Recent studies have shown that online users tend to select information adheres their system of beliefs, ignore does not, and join groups share a common narrative. This environment can elicit tribalism instead informed debate, especially when issues are controversial. Algorithmic solutions, fact-checking initiatives, many other approaches limitations in dealing with this phenomenon, heated debate polarization still play pivotal role social dynamics (e.g. traditional vs....
The massive diffusion of social media fosters disintermediation and changes the way users are informed, they process reality, engage in public debate. cognitive layer related dynamics define nature dimension informational threats. Users show tendency to interact with information adhering their preferred narrative ignore dissenting information. Confirmation bias seems account for decisions about consuming spreading content; and, at same time, aggregation favored within those communities...
How information consumption affects behaviour is an open and widely debated research question. A popular hypothesis states that the so-called infodemic has a substantial impact on orienting individual decisions. competing stresses exposure to vast amounts of even contradictory little effect personal choices. The COVID-19 pandemic offered opportunity investigate this relationship, analysing interplay between related circulation propensity users get vaccinated. We analyse vaccine infodemics...
Abstract Periods of financial turmoil are not only characterized by higher correlation across assets but also modifications in their overall clustering structure. In this work, we develop a dynamic Latent-Space mixture model for capturing changes the structure at fine scale. Through model, able to project stocks onto lower dimensional manifold and detect presence clusters. The infinite-mixture assumption ensures tractability inference accommodates cases which number clusters is large....
The techniques suggested in Fr\"uhwirth-Schnatter et al. (2024) concern sparsity and factor selection have enormous potential beyond standard analysis applications. We show how these can be applied to Latent Space (LS) models for network data. These suffer from well-known identification issues of the latent factors due likelihood invariance translation, reflection, rotation (see Hoff al., 2002). A set observables instrumental identifying via auxiliary equations Liu 2021). These, turn, share...
Latent Space (LS) network models project the nodes of a on $d$-dimensional latent space to achieve dimensionality reduction while preserving its relevant features. Inference is often carried out within Markov Chain Monte Carlo (MCMC) framework. Nonetheless, it well-known that computational time for this set increases quadratically with number nodes. In work, we build Random-Scan (RS) approach propose an MCMC strategy alleviates burden LS maintaining benefits general-purpose technique. We...
Reply to Comment on “The COVID-19 infodemic does not affect vaccine acceptance”, appeared OSF preprints, July 23, 2021 by Gallotti et al.
One of the most pressing challenges in digital media landscape is understanding impact biases on news sources that people rely for information. Biased can have significant and far-reaching consequences, influencing our perspectives shaping decisions we make, potentially endangering public individual well-being. With advent Internet social media, discussions moved online, making it easier to disseminate both accurate inaccurate To combat mis- dis-information, many begun evaluate reliability...
News outlets are now more than ever incentivized to provide their audience with slanted news, while the intrinsic homophilic nature of online social media may exacerbate polarized opinions. Here, we propose a new dynamic latent space model for time-varying audience-duplication networks, which exploits content conduct inference on bias and polarization news outlets. Our contributes literature in several directions: 1) model-embedded data-driven interpretation leaning terms bias; 2) endow our...
An amendment to this paper has been published and can be accessed via a link at the top of paper.