
Marco BrambillaPolitecnico di Milano | Polimi · Department of Electronics, Information, and Bioengineering
Marco Brambilla
Ph.D. in Information Engineering
About
379
Publications
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Introduction
I'm now on:
- Data Science for social media analytics and societal impact
- Crowdsourcing and social sourcing
- Model-driven development of UI /UX and mobile (IFML)
- startups with www.Fluxedo.com and www.WebRatio.com
Additional affiliations
September 2011 - present

Independent Researcher
Position
- BPM4People
January 2008 - present
Publications
Publications (379)
Social media provides many opportunities to monitor and evaluate political phenomena such as referendums and elections. In this study, we propose a set of approaches to analyze long-running political events on social media with a real-world experiment: the debate about Brexit, i.e., the process through which the United Kingdom activated the option...
This paper presents a user modeling pipeline to analyze discussions and opinions shared on social media regarding polarized political events (e.g., public polls). The pipeline follows a four-step methodology. First, social media posts and users metadata are crawled. Second, a filtering mechanism is applied to filter spammers and bot users. As a thi...
In this paper we propose a data augmentation method for time series with irregular sampling, Time-Conditional Generative Adversarial Network (T-CGAN). Our approach is based on Conditional Generative Adversarial Networks (CGAN), where the generative step is implemented by a deconvolutional NN and the discriminative step by a convolutional NN. Both t...
Convolutional Neural Networks (CNNs) have seen significant performance improvements in recent years. However, due to their size and complexity, they function as black-boxes, leading to transparency concerns. State-of-the-art saliency methods generate local explanations that highlight the area in the input image where a class is identified but canno...
Aerospace manufacturing companies, such as Thales Alenia Space, design, develop, integrate, verify, and validate products characterized by high complexity and low volume. They carefully document all phases for each product but analyses across products are challenging due to the heterogeneity and unstructured nature of the data in documents. In this...
Transparency and explainability in image classification are essential for establishing trust in machine learning models and detecting biases and errors. State-of-the-art explainability methods generate saliency maps to show where a specific class is identified, without providing a detailed explanation of the model's decision process. Striving to ad...
Digitally-supported participatory methods are often used in policy-making to develop inclusive policies by collecting and integrating citizen's opinions. However, these methods fail to capture the complexity and nuances in citizen's needs, i.e., citizens are generally unaware of other's needs, perspectives, and experiences. Consequently, policies d...
This work focuses on human-AI interactions, employing a crowd-based methodology to collect and assess the reactions and perceptions of a human audience to a dialogue between a human and an artificial intelligent agent. The study is conducted through a live streaming platform where human streamers broadcast interviews to a custom-made GPT voice inte...
Despite the impressive performance of Artificial Intelligence (AI) systems, their robustness remains elusive and constitutes a key issue that impedes large-scale adoption. Besides, robustness is interpreted differently across domains and contexts of AI. In this work, we systematically survey recent progress to provide a reconciled terminology of co...
Conversational user interfaces (CUIs), such as chatbots, are becoming a common component of many software systems. Although they are evolving in many directions (such as advanced language processing features, thanks to new AI-based developments), less attention has been paid to access control and other security concerns associated with CUIs, which...
The investigation of users’ behaviour on Web and Social Media platforms usually requires to analyze many heterogeneous features, such as shared textual content, social connections, demographic traits, and temporal attributes. This work aims to compute accurate user similarities on Twitter just using the textual content shared by users, a feature kn...
Machine learning (ML) practitioners and organizations are building model repositories of pre-trained models, referred to as
model zoos
. These model zoos contain metadata describing the properties of the ML models and datasets. The metadata serves crucial roles for reporting, auditing, ensuring reproducibility, and enhancing interpretability. Des...
The rapid proliferation of social media has been redefining every facet of the old marketing and customer engagement tactics, not only for low-end and mass-market products but also for luxury brands. In this context, brands are dealing with the challenge of maintaining a balance between using mass marketing strategies concurrent with accentuating t...
The rapid penetration of social media has been redefining every facet of the old marketing and customer engagement tactics, not only for the low-end and mass products but also for luxury brands. In this context, brands are dealing with the challenge of keeping the balance between using mass marketing strategies concurrent with accentuating the excl...
Despite the impressive performance of Artificial Intelligence (AI) systems, their robustness remains elusive and constitutes a key issue that impedes large-scale adoption. Robustness has been studied in many domains of AI, yet with different interpretations across domains and contexts. In this work, we systematically survey the recent progress to p...
Social media platforms offer their audience the possibility to reply to posts through comments and reactions. This allows social media users to express their ideas and opinions on shared content, thus opening virtual discussions. Most studies on social networks have focused only on user relationships or on the shared content, while ignoring the val...
As the performance and complexity of machine learning models have grown significantly over the last years, there has been an increasing need to develop methodologies to describe their behaviour. Such a need has mainly arisen due to the widespread use of black-box models, i.e., high-performing models whose internal logic is challenging to describe a...
Despite the increasing limitations for unvaccinated people, in many European countries there is still a non-negligible fraction of individuals who refuse to get vaccinated against SARS-CoV-2, undermining governmental efforts to eradicate the virus. We study the role of online social media in influencing individuals' opinion towards getting vaccinat...
EmpathiCH aims at bringing together and blend different expertise to develop new research agenda in the context of "Empathy-Centric Design at Scale". The main research question is to investigate how new technologies can contribute to the elicitation of empathy across and within multiple stakeholders at scale; and how empathy can be used to design s...
Traditional approaches to data-informed policymaking are often tailored to specific contexts and lack strong citizen involvement and collaboration, which are required to design sustainable policies. We argue the importance of empathy-based methods in the policymaking domain given the successes in diverse settings, such as healthcare and education....
The spread of AI and black-box machine learning models made it necessary to explain their behavior. Consequently, the research field of Explainable AI was born. The main objective of an Explainable AI system is to be understood by a human as the final beneficiary of the model. In our research, we frame the explainability problem from the crowds poi...
Despite the increasing limitations for unvaccinated people, in many European countries there is still a non-negligible fraction of individuals who refuse to get vaccinated against SARS-CoV-2, undermining governmental efforts to eradicate the virus. We study the role of online social media in influencing individuals' opinion towards getting vaccinat...
Conversational User Interfaces (CUIs), such as chatbots, are becoming a common component of many software systems and they are evolving in many directions (including advanced features, often powered by AI-based components). However, less attention has been paid to their security aspects, such as access-control, which may pose a clear risk. In this...
Chapter “A Web-Based Co-Creation and User Engagement Method and Platform” was previously published non-open access. It has now been changed to open access under a CC BY 4.0 license and the copyright holder updated to ‘The Author(s)’. The book has also been updated with this change.
Background:
There is increasing evidence that a complex interplay of factors within environments in which children grows up, contributes to children's suboptimal mental health and cognitive development. The concept of the life-course exposome helps to study the impact of the physical and social environment, including social inequities, on cognitiv...
In the cultural tourism field, there has been an increasing interest in adopting data-driven approaches that are aimed at measuring the service quality dimensions through online reviews. To date, studies measuring quality dimensions in cultural tourism settings through content analysis of online user-generated reviews are mainly based on manual app...
For applications that have not yet been launched, a reliable way for creating online navigation logs may be crucial, enabling developers to test their products as though they were being used by real users. This might lead to faster and lower-cost program testing and enhancement, especially in terms of usability and interaction. In this work we prop...
Semantic sentence embeddings are usually supervisedly built minimizing distances between pairs of embeddings of sentences labelled as semantically similar by annotators. Since big labelled datasets are rare, in particular for non-English languages, and expensive, recent studies focus on unsupervised approaches that require not-paired input sentence...
The growth of social media and the resulting increase of user generated content attracted people coming from different fields interested in analyzing this kind of data. Recently user generated content has been used for environmental monitoring. In this paper, we propose a model-driven approach for developing social media applications for environmen...
Cities are growing as melting pots of people with different culture, religion, and language. In this paper, through multilingual analysis of Twitter contents shared within a city, we analyze the prevalent language in the different neighborhoods of the city and we compare the results with census data, in order to highlight any parallelisms or discre...
Software systems start to include other types of interfaces beyond the “traditional” Graphical-User Interfaces (GUIs). In particular, Conversational User Interfaces (CUIs) such as chat and voice are becoming more and more popular. These new types of interfaces embed smart natural language processing components to understand user requests and respon...
In the last few years, thanks to the emergence of Web 2.0, social media has made the concept of online live events possible. Users participate more and more in long-running recurring events in social media by sharing their experiences and desires. In the last few years, thanks to the emergence of Web 2.0, social media has made the concept of online...
In recent years, new methods to engage citizens in deliberative processes of governments and institutions have been studied. Such methodologies have become a necessity to assure the efficacy and longevity of policies. Several tools and solutions have been proposed while trying to achieve such a goal. The dual problem to citizen engagement is how to...
In online social media platforms, users can express their ideas by posting original content or by adding comments and responses to existing posts, thus generating virtual discussions and conversations. Studying these conversations is essential for understanding the online communication behavior of users. This study proposes a novel approach to retr...
In this work, we propose a virtual assistant that allows building models by means of voice commands. To demonstrate the generality of the approach, we describe three alternative strategies that apply voice-based support at three levels of detail: a fully-guided strategy; a pattern-based strategy; and an element-based strategy. We describe our imple...
The advent of social media platforms has caused many changes in humans’ daily lifestyle. One of the most significant changes is the way in which people participate in social and cultural events. Users' participation in social media platforms is continuously increasing. This has provided brands with new opportunities such as enhancing brand influenc...
We monitor online conversations of Italian users around vaccines on Twitter, and we provide public access to the on-going data collection which will run continuously throughout the vaccination campaign in Italy. We started collecting tweets matching vaccine-related keywords (in Italian) on December 20th 2020 using Twitter APIs, capturing the offici...
Large pre-trained language representation models (LMs) have recently collected a huge number of successes in many NLP tasks.
In 2018 BERT, and later its successors (e.g. RoBERTa), obtained state-of-the-art results in classical benchmark tasks, such as GLUE.
Works about adversarial attacks have been published to test their generalization proprieti...
Studying the dynamics of COVID-19 is of paramount importance to understanding the efficiency of restrictive measures and develop strategies to defend against upcoming contagion waves. In this work, we study the spread of COVID-19 using a semi-supervised neural network and assuming a passive part of the population remains isolated from the virus dyn...
Nowadays controversial topics on social media are often linked to hate speeches, fake news propagation, and biased or misinformation spreading. Detecting controversy in online discussions is a challenging task, but essential to stop these unhealthy behaviours. In this work, we develop a general pipeline to quantify controversy on social media throu...
Progress in proteomics has enabled biologists to accurately measure the amount of protein in a tumor. This work is based on a breast cancer data set, result of the proteomics analysis of a cohort of tumors carried out at Karolinska Institutet. While evidence suggests that an anomaly in the protein content is related to the cancerous nature of tumor...
In this work, we present a method to extract new knowledge from content shared by users on social networks, with particular emphasis on extraction of evolving relations between entities. Our method combines natural language processing and machine learning for extracting relations in the form of triples (subject-relation-object). The method works on...
A robust technique for generating web navigation logs could be fundamental for applications not yet released, since developers could evaluate their applications as if they were used by real clients. This could allow to test and improve the applications faster and with lower costs, especially with respect to the usability and interaction aspects. In...
Online social media platforms have become a major place where people also discuss their opinions and express their feelings about socio-political phenomena such as elections and referendums. Human-generated online content is a fruitful resource for a deeper understanding of these happenings. In this study, we present a dataset comprising 45 months...
Dataset reporting posts and users on Instagram about 2018 fashion weeks.
This book constitutes the thoroughly refereed post-workshop proceedings of the 19th International Conference on Web Engineering, ICWE 2019, held in Daejeon, South Korea, in June 2019. The 11 revised full papers were selected from 25 submissions. The workshops complement the main conference and explore new trends on core topics of Web engineering an...
Nowadays social networks are becoming an essential ingredient of our life, the faster way to share ideas and to influence people. Interaction within social networks tends to take place within communities, sets of social accounts which share friendships, ideas, interests and passions; detecting digital communities is of increasing relevance, from a...
The network of collaborations in an open source project can reveal relevant emergent properties that influence its prospects of success. In this work, we analyze open source projects to determine whether they exhibit a rich-club behavior, i.e., a phenomenon where contributors with a high number of collaborations (i.e., strongly connected within the...
Online social media are changing the news industry and revolutionizing the traditional role of journalists and newspapers. In this scenario, investigating the behaviour of users in relationship to news sharing is relevant, as it provides means for understanding the impact of online news, their propagation within social communities, their impact on...
Image quality plays a big role in CNN-based image classification performance. Fine-tuning the network with distorted samples may be too costly for large networks. To solve this issue, we propose a transfer learning approach optimized to keep into account that in each layer of a CNN some filters are more susceptible to image distortion than others....
With the increase of digital interaction, social networks are becoming an essential ingredient of our life, by progressively becoming the dominant media, e.g. in influencing political choices. Interaction within social networks tends to take place within communities, sets of social accounts which share friendships, ideas, interests and passions; de...
In a world more and more connected, new and complex interaction patterns can be extracted in the communication between people. This is extremely valuable for brands that can better understand the interests of users and the trends on social media to better target their products. In this paper, we aim to analyze the communities that arise around comm...
Welcome to this special issue of the Semantic Web (SWJ) journal. The special issue compiles three technical contributions that significantly advance the state-of-the-art in exploration of semantic data using semantic web techniques and technologies.
Cities can be observed through a broad set of sensing technologies, spanning from physical sensors in the streets, to socio-economic reports, to other kinds of sources that are able to represent the behaviour of the citizens and visitors, such as mobile phone records, social media posts, and other digital traces.
In this paper, we propose a concept...
This paper presents a user modeling pipeline to analyze discussions and opinions shared on social media regarding polarized political events (e.g., public polls). The pipeline follows a four-step methodology. First, social media posts and users metadata are crawled. Second, a filtering mechanism is applied to filter spammers and bot users. As a thi...
Social media platforms let users share their opinions through textual or multimedia content. In many settings, this becomes a valuable source of knowledge that can be exploited for specific business objectives. In this work, we report on an implementation aiming at cleaning the data collected from social content, within specific domains or related...
Data management is continuously evolving for serving the needs of an increasingly connected society. New challenges apply not only to systems and technology, but also to the models and abstractions for capturing new application requirements. In this paper, we describe several models and abstractions which have been progressively designed to capture...