Michele Coscia

• University of Pisa

Recent advances in archaeogenomics have granted access to previously unavailable biological information with the potential to further our understanding of past social dynamics at a range of scales. However, to properly integrate these data within archaeological narratives, new methodological and theoretical tools are required. Effort must be put in...

Cultural data analytics aims to use analytic methods to explore cultural expressions—for instance art, literature, dance, music. The common thing between cultural expressions is that they have multiple qualitatively different facets that interact with each other in non trivial and non learnable ways. To support this observation, we use the Italian...

An intensely debated topic is whether political polarization on social media is on the rise. We can investigate this question only if we can quantify polarization, by taking into account how extreme the opinions of the people are, how much they organize into echo chambers, and how these echo chambers organize in the network. Current polarization es...

Many people use social media as a primary information source, but their questionable reliability has pushed platforms to contain misinformation via crowdsourced flagging systems. Such systems, however, assume that users are impartial arbiters of truth. This assumption might be unwarranted, as users might be influenced by their own political biases...

Estimating the distance covered by a spreading event on a network can lead to a better understanding of epidemics, economic growth, and human behavior. There are many methods solving this problem – which has been called Node Vector Distance (NVD) – for single layer networks. However, many phenomena are better represented by multilayer networks: net...

Social media represent an important source of news for many users. They are, however, affected by misinformation and they might be playing a role in the growth of political polarization. In this paper, we create an agent based model to investigate how policing content and backlash on social media (i.e. conflict) can lead to an increase in polarizat...

Complex networks are useful tools to understand propagation events like epidemics, word-of-mouth, adoption of habits and innovations. Estimating the correlation between two processes happening on the same network is therefore an important problem with a number of applications. However, at present there is no way to do so: current methods either cor...

We describe a problem in complex networks we call the Node Vector Distance (NVD) problem, and we survey algorithms currently able to address it. Complex networks are a useful tool to map a non-trivial set of relationships among connected entities, or nodes. An agent—e.g., a disease—can occupy multiple nodes at the same time and can spread through t...

We use aggregated and anonymized information based on international expenditures through corporate payment cards to map the network of global business travel. We combine this network with information on the industrial composition and export baskets of national economies. The business travel network helps to predict which economic activities will gr...

Many people view news on social media, yet the production of news items online has come under fire because of the common spreading of misinformation. Social media platforms police their content in various ways. Primarily they rely on crowdsourced ‘flags’: users signal to the platform that a specific news item might be misleading and, if they raise...

Discovering communities in complex networks means grouping nodes similar to each other, to uncover latent information about them. There are hundreds of different algorithms to solve the community detection task, each with its own understanding and definition of what a "community" is. Dozens of review works attempt to order such a diverse landscape...

International aid is a complex system: it involves different issues, countries, and donors. In this paper, we use web crawling to collect information about the activities of international aid organizations on different health-related topics and network analysis to depict this complex system of relationships among organizations. By systematically co...

The global trade system can be viewed as a dynamic ecosystem in which exporters struggle for resources: the markets in which they export. We can think that the aim of an exporter is to gain the entirety of a market share (say, car imports from the United States). This is similar to the objective of an organism in its attempt to monopolize a given s...

The file contains the data and code to reproduce the main results in the paper, namely Table 1 and Fig 8. (ZIP)

The SITC product classification legend, showing the correspondence between each product code and its label. (PDF)

Complex networks are a useful tool for the understanding of complex systems. One of the emerging properties of such systems is their tendency to form hierarchies: networks can be organized in levels, with nodes in each level exerting control on the ones beneath them. In this paper, we focus on the problem of estimating how hierarchical a directed n...

Data and code for result replication. The ZIP file contains the data and code necessary to reproduce the figures and tables in the paper, along with an implementation of all the hierarchy methods discussed. The file contains a README file for a deeper explanation on how to use the provided material. (ZIP)

Clustering is the subset of data mining techniques used to agnostically classify entities by looking at their attributes. Clustering algorithms specialized to deal with complex networks are called community discovery. Notwithstanding their common objectives, there are crucial assumptions in community discovery-edge sparsity and only one node type,...

Tourism is one of the most important economic activities in the world: for many countries it represents the single largest product in their export basket. However, it is a product difficult to chart: "exporters" of tourism do not ship it abroad, but they welcome importers inside the country. Current research uses social accounting matrices and gene...

Real world events are intrinsically dynamic and analytic techniques have to take into account this dynamism. This aspect is particularly important on complex network analysis when relations are channels for interaction events between actors. Sensing technologies open the possibility of doing so for sport networks, enabling the analysis of team perf...

One of the most used measures of the economic health of a nation is the Gross Domestic Product (GDP): the market value of all officially recognized final goods and services produced within a country in a given period of time. GDP, prosperity and well-being of the citizens of a country have been shown to be highly correlated. However, GDP is an impe...

Human behavior is predictable in principle: people are systematic in their everyday choices. This predictability can be used to plan events and infrastructure, both for the public good and for private gains. In this paper we investigate the largely unexplored relationship between the systematic behavior of a customer and its profitability for a ret...

Human behavior is predictable in principle: people are systematic in their everyday choices. This predictability can be used to plan events and infrastructure, both for the public good and for private gains. In this paper we investigate the largely unexplored relationship between the systematic behavior of a customer and its profitability for a ret...

Aim of this paper is to introduce the complex system perspective into retail market analysis. Currently, to understand the retail market means to search for local patterns at the micro level, involving the segmentation, separation and profiling of diverse groups of consumers. In other contexts, however, markets are modelled as complex systems. Such...

Community discovery in complex networks is the task of organizing a network's structure by grouping together nodes related to each other. Traditional approaches are based on the assumption that there is a global-level organization in the network. However, in many scenarios, each node is the bearer of complex information and cannot be classified in...

The availability of massive network and mobility data from diverse domains has fostered the analysis of human behavior and interactions. This data availability leads to challenges in the knowledge discovery community. Several different analyses have been performed on the traces of human trajectories, such as understanding the real borders of human...

In recent years we witnessed the explosion in the availability of data regarding human and customer behavior in the market. This data richness era has fostered the development of useful applications in understanding how markets and the minds of the customers work. In this paper we focus on the analysis of complex networks based on customer behavior...

One classic problem definition in social network analysis is the study of diffusion in networks, which enables us to tackle problems like favoring the adoption of positive technologies. Most of the attention has been turned to how to maximize the number of influenced nodes, but this approach misses the fact that different scenarios imply different...

Complex networks have been receiving increasing attention by the scientific community, thanks also to the increasing availability of real-world network data. So far, network analysis has focused on the characterization and measurement of local and global properties of graphs, such as diameter, degree distribution, centrality, and so on. In the last...

In our market society, buyers are considered rational entities, driven by two utility functions: i) the amount of money spent, a universal quantity to be minimized; and ii) the individual needs to satisfy, a personal quantity, varying from person to person, to be maximized. In this paper, we propose an analytic framework based on big data to measur...

Finding talents, often among the people already hired, is an endemic challenge for organizations. The social networking revolution, with online tools like Linkedin, made possible to make explicit and accessible what we perceived, but not used, for thousands of years: the exact position and ranking of a person in a network of professional and person...

The advent of social media has provided data and insights about how people relate to information and culture. While information is composed by bits and its fundamental building bricks are relatively well understood, the same cannot be said for culture. The fundamental cultural unit has been defined as a "meme". Memes are defined in literature as sp...

Within the large body of research in complex network analysis, an important topic is the temporal evolution of networks. Existing approaches aim at analyzing the evolution on the global and the local scale, extracting properties of either the entire network or local patterns. In this paper, we focus on detecting clusters of temporal snapshots of a...

Online social networks are increasingly being used as places where communities gather to exchange information, form opinions, collaborate in response to events. An aspect of this information exchange is how to determine if a source of social information can be trusted or not. Data mining literature addresses this problem. However, if usually employ...

Community discovery in complex networks is an interesting problem with a number of applications, especially in the knowledge extraction task in social and information networks. However, many large networks often lack a particular community organization at a global level. In these cases, traditional graph partitioning algorithms fail to let the late...

The availability of massive network and mobility data from diverse domains has fostered the analysis of human behavior and interactions. Broad, extensive, and multidisciplinary research has been devoted to the extraction of non-trivial knowledge from this novel form of data. We propose a general method to determine the influence of social and mobil...

The availability of massive network and mobility data from diverse domains has fostered the analysis of human behaviors and interactions. This data availability leads to challenges in the knowledge discovery community. Several different analyses have been performed on the traces of human trajectories, such as understanding the real borders of human...

To detect groups in networks is an interesting problem with applications in social and security analysis. Many large networks lack a global community organization. In these cases, traditional partitioning algorithms fail to detect a hidden modular structure, assuming a global modular organization. We define a prototype for a simple local-first appr...

To explore the demand side of micro economy describing product connections via the customers buying them, as in the macro economy analysis of the supply side.

Community Discovery in networks is the problem of detecting, for each node, its membership to one of more groups of nodes, the communities, that are densely connected, or highly interactive. We define the community discovery problem in multidimensional networks, where more than one connection may reside between any two nodes. We also introduce two...

In the last few years many real-world networks have been found to show a so-called community structure organization. Much effort has been devoted in the literature to develop methods and algorithms that can efficiently highlight this hidden structure of the network, traditionally by partitioning the graph. Since network representation can be very c...

Hubs are highly connected nodes within a network In complex network analysis, hubs have been widely studied, and are at the basis of many tasks, such as web search and epidemic outbreak detection. In reality, networks are often multidimensional, i.e., there can exist multiple connections between any pair of nodes. In this setting, the concept of hu...

Complex networks have been receiving increasing attention by the scientific community, thanks also to the increasing availability of real-world network data. In the last years, the multidimensional nature of many real world networks has been pointed out, i.e. many networks containing multiple connections between any pair of nodes have been analyzed...

Complex networks have been receiving increasing attention by the scientific community, also due to the availability of massive network data from diverse domains. One problem studied so far in complex network analysis is Community Discovery, i.e. the detection of group of nodes densely connected, or highly related. However, one aspect of such networ...

This work aims to approach the phenomenon of culture through the development of new methods and more powerful tools to capture the content of digitally stored literary material. The authors chose as a test bed Dante's characters of al di là, a domain consisting in a set of data and relations complex enough to sharpen existing tools. The methods of...

Within the large body of research in complex network analysis, an important topic is the temporal evolution of networks. Existing approaches aim at analyzing the evolution on the global and the local scale, extracting properties of either the entire network or local patterns. In this paper, we focus instead on detecting clusters of temporal snapsho...

In the last decades, much research has been devoted in topics related to Social Network Analysis. One important direction in this area is to analyze the temporal evolution of a network. So far, previous approaches analyzed this setting at both the global and the local level. In this paper, we focus on finding a way to detect temporal eras in an evo...

In the last decade, Social Network Analysis has been a field in which the effort devoted from several researchers in the Data Mining area has increased very fast. Among the possible related topics, the study of the information propagation in a network attracted the interest of many researchers, also from the industrial world. However, only a few an...

Today digital bibliographies are a powerful instrument that collects a great amount of data about scientific publications. Digital bibliographies have been used as basis of many studies focused on the knowledge extraction in databases. Here we present anew methodology for mining knowledge in this field. Our approach aims to apply the potential of s...

In the last decade, Social Network Analysis has been a field in which the effort devoted from several researchers in the Data Mining area has increased very fast. Among the possible related topics, the study of the information propagation in a network attracted the interest of many researchers, also from the industrial world. However, only a few an...