1. Marco Bardoscia, Stefano Battiston, Fabio Caccioli and Guido Caldarelli. DebtRank: A Microscopic Foundation for Shock Propagation (vol 10, e0130406, 2015). PLOS ONE 10(7), July 2015. DOI BibTeX

    @article{ISI:000358838400185,
    	author = "Bardoscia, Marco and Battiston, Stefano and Caccioli, Fabio and Caldarelli, Guido",
    	doi = "10.1371/journal.pone.0134888",
    	issn = "1932-6203",
    	journal = "PLOS ONE",
    	month = "jul",
    	number = 7,
    	title = "{DebtRank: A Microscopic Foundation for Shock Propagation (vol 10, e0130406, 2015)}",
    	volume = 10,
    	year = 2015
    }
    
  2. Juan Ignacio Perotti, Claudio Juan Tessone and Guido Caldarelli. Hierarchical mutual information for the comparison of hierarchical community structures in complex networks. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 92(6):1–13, 2015. URL, DOI BibTeX

    @article{Perotti2015,
    	abstract = "The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the {\{}$\backslash$it hierarchical mutual information{\}}, which is a generalization of the traditional mutual information, and allows to compare hierarchical partitions and hierarchical community structures. The {\{}$\backslash$it normalized{\}} version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here, the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies, and on the hierarchical community structure of artificial and empirical networks. Furthermore, the experiments illustrate some of the practical applications of the hierarchical mutual information. Namely, the comparison of different community detection methods, and the study of the the consistency, robustness and temporal evolution of the hierarchical modular structure of networks.",
    	archiveprefix = "arXiv",
    	arxivid = "1508.04388",
    	author = "Perotti, Juan Ignacio and Tessone, Claudio Juan and Caldarelli, Guido",
    	doi = "10.1103/PhysRevE.92.062825",
    	eprint = "1508.04388",
    	isbn = "1539-3755",
    	issn = 15502376,
    	journal = "Physical Review E - Statistical, Nonlinear, and Soft Matter Physics",
    	keywords = "DOLFINS{\_}T2.1,DOLFINS{\_}WP2",
    	mendeley-tags = "DOLFINS{\_}T2.1,DOLFINS{\_}WP2",
    	number = 6,
    	pages = "1--13",
    	pmid = 26764762,
    	title = "{Hierarchical mutual information for the comparison of hierarchical community structures in complex networks}",
    	url = "http://journals.aps.org/pre/abstract/10.1103/PhysRevE.92.062825",
    	volume = 92,
    	year = 2015
    }
    
  3. Chiara Orsini, Marija M Dankulov, Pol Colomer-de-Simón, Almerima Jamakovic, Priya Mahadevan, Amin Vahdat, Kevin E Bassler, Zoltán Toroczkai, Marián Boguñá, Guido Caldarelli, Santo Fortunato and Dmitri Krioukov. Quantifying randomness in real networks. Nature Communications 6(May):8627, 2015. URL, DOI BibTeX

    @article{orsini2015quantifying,
    	abstract = "Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks—the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain—and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs.",
    	archiveprefix = "arXiv",
    	arxivid = "1505.07503",
    	author = "Orsini, Chiara and Dankulov, Marija M. and Colomer-de-Sim{\'{o}}n, Pol and Jamakovic, Almerima and Mahadevan, Priya and Vahdat, Amin and Bassler, Kevin E. and Toroczkai, Zolt{\'{a}}n and Bogu{\~{n}}{\'{a}}, Mari{\'{a}}n and Caldarelli, Guido and Fortunato, Santo and Krioukov, Dmitri",
    	doi = "10.1038/ncomms9627",
    	eprint = "1505.07503",
    	file = ":Users/Gcalda/Google Drive (This email address is being protected from spambots. You need JavaScript enabled to view it.)/Mendeley Desktop/Orsini et al/Nature Communications/Orsini et al. - 2015 - Quantifying randomness in real networks.pdf:pdf",
    	isbn = 0123145627,
    	issn = "2041-1723",
    	journal = "Nature Communications",
    	number = "May",
    	pages = 8627,
    	pmid = 26482121,
    	title = "{Quantifying randomness in real networks}",
    	url = "http://www.nature.com/ncomms/2015/151020/ncomms9627/full/ncomms9627.html",
    	volume = 6,
    	year = 2015
    }
    
  4. Fabiana Zollo, Petra Kralj Novak, Michela Del Vicario, Alessandro Bessi, Igor Mozetič, Antonio Scala, Guido Caldarelli and Walter Quattrociocchi. Emotional Dynamics in the Age of Misinformation. PLOS ONE 10(9):e0138740, September 2015. URL BibTeX

    @article{zollo2015emotional,
    	author = "Zollo, Fabiana and Novak, Petra Kralj and {Del Vicario}, Michela and Bessi, Alessandro and Mozeti{\v{c}}, Igor and Scala, Antonio and Caldarelli, Guido and Quattrociocchi, Walter",
    	editor = "Preis, Tobias",
    	file = "::",
    	issn = "1932-6203",
    	journal = "PLOS ONE",
    	month = "sep",
    	number = 9,
    	pages = "e0138740",
    	publisher = "Public Library of Science",
    	title = "{Emotional Dynamics in the Age of Misinformation}",
    	url = "http://journals.plos.org/plosone/article?id=10.1371{\%}2Fjournal.pone.0138740",
    	volume = 10,
    	year = 2015
    }
    
  5. Michele Borassi, Alessandro Chessa and Guido Caldarelli. Hyperbolicity Measures “ Democracy ” in Real-World Networks. Physcal Review E 92:032812, 2015. BibTeX

    @article{Borassi2015,
    	author = "Borassi, Michele and Chessa, Alessandro and Caldarelli, Guido",
    	file = ":Users/Gcalda/Google Drive (This email address is being protected from spambots. You need JavaScript enabled to view it.)/Mendeley Desktop/Borassi, Chessa, Caldarelli/Physcal Review E/Borassi, Chessa, Caldarelli - 2015 - Hyperbolicity Measures “ Democracy ” in Real-World Networks.pdf:pdf",
    	journal = "Physcal Review E",
    	pages = 032812,
    	title = "{Hyperbolicity Measures “ Democracy ” in Real-World Networks}",
    	volume = 92,
    	year = 2015
    }
    
  6. Gabriele Ranco, Darko Aleksovski, Guido Caldarelli, Miha Grčar and Igor Mozetič. The Effects of Twitter Sentiment on Stock Price Returns.. PloS one 10(9):e0138441, January 2015. URL, DOI BibTeX

    @article{Ranco2015,
    	abstract = {Social media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-known micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment about the 30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We find a relatively low Pearson correlation and Granger causality between the corresponding time series over the entire time period. However, we find a significant dependence between the Twitter sentiment and abnormal returns during the peaks of Twitter volume. This is valid not only for the expected Twitter volume peaks (e.g., quarterly announcements), but also for peaks corresponding to less obvious events. We formalize the procedure by adapting the well-known "event study" from economics and finance to the analysis of Twitter data. The procedure allows to automatically identify events as Twitter volume peaks, to compute the prevailing sentiment (positive or negative) expressed in tweets at these peaks, and finally to apply the "event study" methodology to relate them to stock returns. We show that sentiment polarity of Twitter peaks implies the direction of cumulative abnormal returns. The amount of cumulative abnormal returns is relatively low (about 1-2{\%}), but the dependence is statistically significant for several days after the events.},
    	author = "Ranco, Gabriele and Aleksovski, Darko and Caldarelli, Guido and Gr{\v{c}}ar, Miha and Mozeti{\v{c}}, Igor",
    	doi = "10.1371/journal.pone.0138441",
    	issn = "1932-6203",
    	journal = "PloS one",
    	month = "jan",
    	number = 9,
    	pages = "e0138441",
    	pmid = 26390434,
    	publisher = "Public Library of Science",
    	title = "{The Effects of Twitter Sentiment on Stock Price Returns.}",
    	url = "http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0138441",
    	volume = 10,
    	year = 2015
    }
    
  7. Mario Mureddu, Guido Caldarelli, Alessandro Chessa, Antonio Scala and Alfonso Damiano. Green Power Grids: How Energy from Renewable Sources Affects Networks and Markets.. PloS one 10(9):e0135312, January 2015. URL BibTeX

    @article{mureddu2015green,
    	abstract = "The increasing attention to environmental issues is forcing the implementation of novel energy models based on renewable sources. This is fundamentally changing the configuration of energy management and is introducing new problems that are only partly understood. In particular, renewable energies introduce fluctuations which cause an increased request for conventional energy sources to balance energy requests at short notice. In order to develop an effective usage of low-carbon sources, such fluctuations must be understood and tamed. In this paper we present a microscopic model for the description and for the forecast of short time fluctuations related to renewable sources in order to estimate their effects on the electricity market. To account for the inter-dependencies in the energy market and the physical power dispatch network, we use a statistical mechanics approach to sample stochastic perturbations in the power system and an agent based approach for the prediction of the market players' behavior. Our model is data-driven; it builds on one-day-ahead real market transactions in order to train agents' behaviour and allows us to deduce the market share of different energy sources. We benchmarked our approach on the Italian market, finding a good accordance with real data.",
    	author = "Mureddu, Mario and Caldarelli, Guido and Chessa, Alessandro and Scala, Antonio and Damiano, Alfonso",
    	file = ":Users/Gcalda/Google Drive (This email address is being protected from spambots. You need JavaScript enabled to view it.)/Mendeley Desktop/Mureddu et al/PloS one/Mureddu et al. - 2015 - Green Power Grids How Energy from Renewable Sources Affects Networks and Markets.pdf:pdf",
    	issn = "1932-6203",
    	journal = "PloS one",
    	month = "jan",
    	number = 9,
    	pages = "e0135312",
    	publisher = "Public Library of Science",
    	title = "{Green Power Grids: How Energy from Renewable Sources Affects Networks and Markets.}",
    	url = "http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0135312",
    	volume = 10,
    	year = 2015
    }
    
  8. Alessandro Bessi, Fabiana Zollo, Michela Del Vicario, Antonio Scala, Guido Caldarelli and Walter Quattrociocchi. Trend of Narratives in the Age of Misinformation. PloS one 10(8):e0134641, January 2015. URL, DOI BibTeX

    @article{Bessi2015a,
    	abstract = "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 disintermediation might weaken consensus on social relevant issues in favor of rumors, mistrust, or conspiracy thinking-e.g., chem-trails inducing global warming, the link between vaccines and autism, or the New World Order conspiracy. Previous studies pointed out that consumers of conspiracy-like content are likely to aggregate in homophile clusters-i.e., echo-chambers. Along this path we study, by means of a thorough quantitative analysis, how different topics are consumed inside the conspiracy echo-chamber in the Italian Facebook. Through a semi-automatic topic extraction strategy, we show that the most consumed contents semantically refer to four specific categories: environment, diet, health, and geopolitics. We find similar consumption patterns by comparing users activity (likes and comments) on posts belonging to these different semantic categories. Finally, we model users mobility across the distinct topics finding that the more a user is active, the more he is likely to span on all categories. Once inside a conspiracy narrative users tend to embrace the overall corpus.",
    	author = "Bessi, Alessandro and Zollo, Fabiana and {Del Vicario}, Michela and Scala, Antonio and Caldarelli, Guido and Quattrociocchi, Walter",
    	doi = "10.1371/journal.pone.0134641",
    	issn = "1932-6203",
    	journal = "PloS one",
    	month = "jan",
    	number = 8,
    	pages = "e0134641",
    	pmid = 26275043,
    	publisher = "Public Library of Science",
    	title = "{Trend of Narratives in the Age of Misinformation}",
    	url = "http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0134641",
    	volume = 10,
    	year = 2015
    }
    
  9. Young-Ho Eom, Michelangelo Puliga, Jasmina Smailovic, Igor Mozetic and Guido Caldarelli. Twitter-Based Analysis of the Dynamics of Collective Attention to Political Parties.. PloS one 10(7):e0131184, January 2015. URL, DOI BibTeX

    @article{Eom2015,
    	abstract = "Large-scale data from social media have a significant potential to describe complex phenomena in the real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the election outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media.",
    	author = "Eom, Young-Ho and Puliga, Michelangelo and Smailovic, Jasmina and Mozetic, Igor and Caldarelli, Guido",
    	doi = "10.1371/journal.pone.0131184",
    	file = "::",
    	issn = "1932-6203",
    	journal = "PloS one",
    	month = "jan",
    	number = 7,
    	pages = "e0131184",
    	pmid = 26161795,
    	publisher = "Public Library of Science",
    	title = "{Twitter-Based Analysis of the Dynamics of Collective Attention to Political Parties.}",
    	url = "http://journals.plos.org/plosone/article?id=10.1371{\%}2Fjournal.pone.0131184",
    	volume = 10,
    	year = 2015
    }
    
  10. Marco Bardoscia, Stefano Battiston, Fabio Caccioli and Guido Caldarelli. DebtRank: A microscopic foundation for shock propagation. PLoS ONE 10(6):e0134888, January 2015. URL, DOI BibTeX

    @article{bardoscia2015debtrank,
    	abstract = {The DebtRank algorithm has been increasingly investigated as a method to estimate the impact of shocks in financial networks, as it overcomes the limitations of the traditional default-cascade approaches. Here we formulate a dynamical "microscopic" theory of instability for financial networks by iterating balance sheet identities of individual banks and by assuming a simple rule for the transfer of shocks from borrowers to lenders. By doing so, we generalise the DebtRank formulation, both providing an interpretation of the effective dynamics in terms of basic accounting principles and preventing the underestimation of losses on certain network topologies. Depending on the structure of the interbank leverage matrix the dynamics is either stable, in which case the asymptotic state can be computed analytically, or unstable, meaning that at least one bank will default. We apply this framework to a dataset of the top listed European banks in the period 2008-2013. We find that network effects can generate an amplification of exogenous shocks of a factor ranging between three (in normal periods) and six (during the crisis) when we stress the system with a 0.5{\%} shock on external (i.e. non-interbank) assets for all banks.},
    	archiveprefix = "arXiv",
    	arxivid = "1504.01857",
    	author = "Bardoscia, Marco and Battiston, Stefano and Caccioli, Fabio and Caldarelli, Guido",
    	doi = "10.1371/journal.pone.0130406",
    	eprint = "1504.01857",
    	issn = 19326203,
    	journal = "PLoS ONE",
    	keywords = "battiston{\_}journals",
    	mendeley-tags = "battiston{\_}journals",
    	month = "jan",
    	number = 6,
    	pages = "e0134888",
    	pmid = 26091013,
    	publisher = "Public Library of Science",
    	title = "{DebtRank: A microscopic foundation for shock propagation}",
    	url = "http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130406",
    	volume = 10,
    	year = 2015
    }
    
  11. Alessandro Bessi, Mauro Coletto, George Alexandru Davidescu, Antonio Scala, Guido Caldarelli and Walter Quattrociocchi. Science vs Conspiracy: Collective Narratives in the Age of Misinformation. Plos One 10(2):e0118093, 2015. URL, DOI BibTeX

    @article{bessi2015science,
    	abstract = "The large availability of user provided contents on online social media facilitates people aggregation around shared beliefs, interests, worldviews and narratives. In spite of the enthusiastic rhetoric about the so called collective intelligence unsubstantiated rumors and conspiracy theories – e.g., chemtrails, reptilians or the Illuminati – are pervasive in online social networks (OSN). In this work we study, on a sample of 1.2 million of individuals, how information related to very distinct narratives – i.e. main stream scientific and conspiracy news – are consumed and shape communities on Facebook. Our results show that polarized communities emerge around distinct types of contents and usual consumers of conspiracy news result to be more focused and self-contained on their specific contents. To test potential biases induced by the continued exposure to unsubstantiated rumors on users' content selection, we conclude our analysis measuring how users respond to 4,709 troll information – i.e. parodistic and sarcastic imitation of conspiracy theories. We find that 77.92{\%} of likes and 80.86{\%} of comments are from users usually interacting with conspiracy stories.",
    	author = "Bessi, Alessandro and Coletto, Mauro and Davidescu, George Alexandru and Scala, Antonio and Caldarelli, Guido and Quattrociocchi, Walter",
    	doi = "10.1371/journal.pone.0118093",
    	file = ":Users/Gcalda/Google Drive (This email address is being protected from spambots. You need JavaScript enabled to view it.)/Mendeley Desktop/Bessi et al/PLoS ONE/Bessi et al. - 2015 - Science vs Conspiracy Collective Narratives in the Age of Misinformation.pdf:pdf",
    	issn = "1932-6203",
    	journal = "Plos One",
    	number = 2,
    	pages = "e0118093",
    	title = "{Science vs Conspiracy: Collective Narratives in the Age of Misinformation}",
    	url = "http://dx.plos.org/10.1371/journal.pone.0118093",
    	volume = 10,
    	year = 2015
    }
    
  12. Alessandro Bessi, Fabio Petroni, Michela Del Vicario, Fabiana Zollo, Aris Anagnostopoulos, Antonio Scala, Guido Caldarelli and Walter Quattrociocchi. Viral Misinformation: The Role of Homophily and Polarization. In Proceedings of the 24th International Conference on World Wide Web - WWW '15 Companion. 2015, 355–356. URL, DOI BibTeX

    @inproceedings{Bessi2015d,
    	address = "New York, New York, USA",
    	annote = "https://simpolproject.eu/download/simpol-initiative-research/anagnostopoulos2014viral.pdf",
    	author = "Bessi, Alessandro and Petroni, Fabio and {Del Vicario}, Michela and Zollo, Fabiana and Anagnostopoulos, Aris and Scala, Antonio and Caldarelli, Guido and Quattrociocchi, Walter",
    	booktitle = "Proceedings of the 24th International Conference on World Wide Web - WWW '15 Companion",
    	doi = "10.1145/2740908.2745939",
    	isbn = 9781450334730,
    	keywords = "big data,misinformation,rumor spreading,social networks,virality",
    	pages = "355--356",
    	publisher = "ACM Press",
    	title = "{Viral Misinformation: The Role of Homophily and Polarization}",
    	url = "http://dl.acm.org/citation.cfm?doid=2740908.2745939",
    	year = 2015
    }
    
  13. Giulio Cimini, Tiziano Squartini, Nicolò Musmeci, Michelangelo Puliga, Andrea Gabrielli, Diego Garlaschelli, Stefano Battiston and Guido Caldarelli. Reconstructing Topological Properties of Complex Networks Using the Fitness Model. Lecture Notes in Computer Science 8852:323–333, 2015. URL, DOI BibTeX

    @article{cimini2015reconstructing,
    	abstract = "A major problem in the study of complex socioeconomic systems is represented by privacy issues—that can put severe limitations on the amount of accessible information, forcing to build models on the basis of incomplete knowledge. In this paper we investigate a novel method to reconstruct global topological properties of a complex network starting from limited information. This method uses the knowledge of an intrinsic property of the nodes (indicated as fitness), and the number of connections of only a limited subset of nodes, in order to generate an ensemble of exponential random graphs that are representative of the real systems and that can be used to estimate its topological properties. Here we focus in particular on reconstructing the most basic properties that are commonly used to describe a network: density of links, assortativity, clusterin",
    	author = "Cimini, Giulio and Squartini, Tiziano and Musmeci, Nicol{\`{o}} and Puliga, Michelangelo and Gabrielli, Andrea and Garlaschelli, Diego and Battiston, Stefano and Caldarelli, Guido",
    	doi = "10.1007/978-3-319-15168-7_41",
    	file = ":Users/Gcalda/Google Drive (This email address is being protected from spambots. You need JavaScript enabled to view it.)/Mendeley Desktop/Cimini et al/Lecture Notes in Computer Science/Cimini et al. - 2015 - Reconstructing Topological Properties of Complex Networks Using the Fitness Model.pdf:pdf",
    	journal = "Lecture Notes in Computer Science",
    	pages = "323--333",
    	title = "{Reconstructing Topological Properties of Complex Networks Using the Fitness Model}",
    	url = "http://link.springer.com/chapter/10.1007/978-3-319-15168-7{\_}41",
    	volume = 8852,
    	year = 2015
    }
    
  14. Maddalena Dilucca, Giulio Cimini, Andrea Semmoloni, Antonio Deiana and Andrea Giansanti. Codon Bias Patterns of E. coli's Interacting Proteins. PLOS ONE 10(11), November 2015. DOI BibTeX

    @article{ISI:000367628500008,
    	abstract = "Synonymous codons, i.e., DNA nucleotide triplets coding for the same amino acid, are used differently across the variety of living organisms. The biological meaning of this phenomenon, known as codon usage bias, is still controversial. In order to shed light on this point, we propose a new codon bias index, CompAI, that is based on the competition between cognate and near-cognate tRNAs during translation, without being tuned to the usage bias of highly expressed genes. We perform a genome-wide evaluation of codon bias for E. coli, comparing CompAI with other widely used indices: tAI, CAI, and Nc. We show that CompAI and tAI capture similar information by being positively correlated with gene conservation, measured by the Evolutionary Retention Index (ERI), and essentiality, whereas, CAI and Nc appear to be less sensitive to evolutionary-functional parameters. Notably, the rate of variation of tAI and CompAI with ERI allows to obtain sets of genes that consistently belong to specific clusters of orthologous genes (COGs). We also investigate the correlation of codon bias at the genomic level with the network features of protein-protein interactions in E. coli. We find that the most densely connected communities of the network share a similar level of codon bias (as measured by CompAI and tAI). Conversely, a small difference in codon bias between two genes is, statistically, a prerequisite for the corresponding proteins to interact. Importantly, among all codon bias indices, CompAI turns out to have the most coherent distribution over the communities of the interactome, pointing to the significance of competition among cognate and near-cognate tRNAs for explaining codon usage adaptation. Notably, CompAI may potentially correlate with translation speed measurements, by accounting for the specific delay induced by wobble-pairing between codons and anticodons.",
    	author = "Dilucca, Maddalena and Cimini, Giulio and Semmoloni, Andrea and Deiana, Antonio and Giansanti, Andrea",
    	doi = "10.1371/journal.pone.0142127",
    	issn = "1932-6203",
    	journal = "PLOS ONE",
    	month = "nov",
    	number = 11,
    	title = "{Codon Bias Patterns of E. coli's Interacting Proteins}",
    	volume = 10,
    	year = 2015
    }
    
  15. Giulio Cimini and Angel Sanchez. How Evolutionary Dynamics Affects Network Reciprocity in Prisoner's Dilemma. JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION 18(2), March 2015. DOI BibTeX

    @article{ISI:000354373800025,
    	abstract = "Cooperation lies at the foundations of human societies, yet why people cooperate remains a conundrum. The issue, known as network reciprocity, of whether population structure can foster cooperative behavior in social dilemmas has been addressed by many, but theoretical studies have yielded contradictory results so far-as the problem is very sensitive to how players adapt their strategy. However, recent experiments with the prisoner's dilemma game played on different networks and in a specific range of payoffs suggest that humans, at least for those experimental setups, do not consider neighbors' payoffs when making their decisions, and that the network structure does not influence the final outcome. In this work we carry out an extensive analysis of different evolutionary dynamics, taking into account most of the alternatives that have been proposed so far to implement players' strategy updating process. In this manner we show that the absence of network reciprocity is a general feature of the dynamics (among those we consider) that do not take neighbors' payoffs into account. Our results, together with experimental evidence, hint at how to properly model real people's behavior.",
    	author = "Cimini, Giulio and Sanchez, Angel",
    	doi = "10.18564/jasss.2726",
    	issn = "1460-7425",
    	journal = "JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION",
    	month = "mar",
    	number = 2,
    	title = "{How Evolutionary Dynamics Affects Network Reciprocity in Prisoner's Dilemma}",
    	volume = 18,
    	year = 2015
    }
    
  16. Giulio Cimini, Claudio Castellano and Angel Sanchez. Dynamics to Equilibrium in Network Games: Individual Behavior and Global Response. PLOS ONE 10(3), March 2015. DOI BibTeX

    @article{ISI:000353889600070,
    	abstract = "Various social contexts can be depicted as games of strategic interactions on networks, where an individual's welfare depends on both her and her partners' actions. Whereas much attention has been devoted to Bayes-Nash equilibria in such games, here we look at strategic interactions from an evolutionary perspective. To this end, we present the results of a numerical simulations program for these games, which allows us to find out whether Nash equilibria are accessible by adaptation of player strategies, and in general to identify the attractors of the evolution. Simulations allow us to go beyond a global characterization of the cooperativeness at equilibrium and probe into individual behavior. We find that when players imitate each other, evolution does not reach Nash equilibria and, worse, leads to very unfavorable states in terms of welfare. On the contrary, when players update their behavior rationally, they self-organize into a rich variety of Nash equilibria, where individual behavior and payoffs are shaped by the nature of the game, the social network's structure and the players' position within the network. Our results allow to assess the validity of mean-field approaches we use to describe the dynamics of these games. Interestingly, our dynamically-found equilibria generally do not coincide with (but show qualitatively the same features of) those resulting from theoretical predictions in the context of one-shot games under incomplete information.",
    	author = "Cimini, Giulio and Castellano, Claudio and Sanchez, Angel",
    	doi = "10.1371/journal.pone.0120343",
    	issn = "1932-6203",
    	journal = "PLOS ONE",
    	month = "mar",
    	number = 3,
    	title = "{Dynamics to Equilibrium in Network Games: Individual Behavior and Global Response}",
    	volume = 10,
    	year = 2015
    }
    
  17. Giulio Cimini, Tiziano Squartini, Diego Garlaschelli and Andrea Gabrielli. Systemic Risk Analysis on Reconstructed Economic and Financial Networks.. Scientific reports 5:15758, January 2015. URL, DOI BibTeX

    @article{cimini2015systemic,
    	abstract = "We address a fundamental problem that is systematically encountered when modeling real-world complex systems of societal relevance: the limitedness of the information available. In the case of economic and financial networks, privacy issues severely limit the information that can be accessed and, as a consequence, the possibility of correctly estimating the resilience of these systems to events such as financial shocks, crises and cascade failures. Here we present an innovative method to reconstruct the structure of such partially-accessible systems, based on the knowledge of intrinsic node-specific properties and of the number of connections of only a limited subset of nodes. This information is used to calibrate an inference procedure based on fundamental concepts derived from statistical physics, which allows to generate ensembles of directed weighted networks intended to represent the real system-so that the real network properties can be estimated as their average values within the ensemble. We test the method both on synthetic and empirical networks, focusing on the properties that are commonly used to measure systemic risk. Indeed, the method shows a remarkable robustness with respect to the limitedness of the information available, thus representing a valuable tool for gaining insights on privacy-protected economic and financial systems.",
    	author = "Cimini, Giulio and Squartini, Tiziano and Garlaschelli, Diego and Gabrielli, Andrea",
    	doi = "10.1038/srep15758",
    	file = ":Users/Gcalda/Google Drive (This email address is being protected from spambots. You need JavaScript enabled to view it.)/Mendeley Desktop/Cimini et al/Scientific reports/Cimini et al. - 2015 - Systemic Risk Analysis on Reconstructed Economic and Financial Networks.pdf:pdf",
    	issn = "2045-2322",
    	journal = "Scientific reports",
    	language = "en",
    	month = "jan",
    	pages = 15758,
    	pmid = 26507849,
    	publisher = "Nature Publishing Group",
    	title = "{Systemic Risk Analysis on Reconstructed Economic and Financial Networks.}",
    	url = "http://www.nature.com/srep/2015/151028/srep15758/full/srep15758.html",
    	volume = 5,
    	year = 2015
    }
    
  18. Giulio Cimini, Tiziano Squartini, Andrea Gabrielli and Diego Garlaschelli. Estimating topological properties of weighted networks from limited information. Physical Review E 92(4):040802, October 2015. URL, DOI BibTeX

    @article{cimini2015estimating,
    	author = "Cimini, Giulio and Squartini, Tiziano and Gabrielli, Andrea and Garlaschelli, Diego",
    	doi = "10.1103/PhysRevE.92.040802",
    	file = ":Users/Gcalda/Google Drive (This email address is being protected from spambots. You need JavaScript enabled to view it.)/Mendeley Desktop/Cimini et al/Physical Review E/Cimini et al. - 2015 - Estimating topological properties of weighted networks from limited information.pdf:pdf",
    	issn = "1539-3755",
    	journal = "Physical Review E",
    	month = "oct",
    	number = 4,
    	pages = 040802,
    	title = "{Estimating topological properties of weighted networks from limited information}",
    	url = "http://link.aps.org/doi/10.1103/PhysRevE.92.040802",
    	volume = 92,
    	year = 2015
    }
    
  19. F Saracco, R Di Clemente, A Gabrielli and L Pietronero. From innovation to diversification: A simple competitive model. PLoS ONE 10(11), 2015. DOI BibTeX

    @article{Saracco2015,
    	abstract = "{\textcopyright} 2015 Saracco et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Few attempts have been proposed in order to describe the statistical features and historical evolution of the export bipartite matrix countries/products. An important standpoint is the introduction of a products network, namely a hierarchical forest of products that models the formation and the evolution of commodities. In the present article, we propose a simple dynamical model where countries compete with each other to acquire the ability to produce and export new products. Countries will have two possibilities to expand their export: innovating, i.e. introducing new goods, namely new nodes in the product networks, or copying the productive process of others, i.e. occupying a node already present in the same network. In this way, the topology of the products network and the country-product matrix evolve simultaneously, driven by the countries push toward innovation.",
    	author = "Saracco, F. and {Di Clemente}, R. and Gabrielli, A. and Pietronero, L.",
    	doi = "10.1371/journal.pone.0140420",
    	issn = 19326203,
    	journal = "PLoS ONE",
    	number = 11,
    	title = "{From innovation to diversification: A simple competitive model}",
    	volume = 10,
    	year = 2015
    }
    
  20. Fabio Saracco, Riccardo Di Clemente, Andrea Gabrielli and Tiziano Squartini. Randomizing bipartite networks: the case of the World Trade Web. Scientific Reports 5:10595, June 2015. URL, DOI BibTeX

    @article{saracco2015randomizing,
    	abstract = "Within the last fifteen years, network theory has been successfully applied both to natural sciences and to socioeconomic disciplines. In particular, bipartite networks have been recognized to provide a particularly insightful representation of many systems, ranging from mutualistic networks in ecology to trade networks in economy, whence the need of a pattern detection-oriented analysis in order to identify statistically-significant structural properties. Such an analysis rests upon the definition of suitable null models, i.e. upon the choice of the portion of network structure to be preserved while randomizing everything else. However, quite surprisingly, little work has been done so far to define null models for real bipartite networks. The aim of the present work is to fill this gap, extending a recently-proposed method to randomize monopartite networks to bipartite networks. While the proposed formalism is perfectly general, we apply our method to the binary, undirected, bipartite representation of the World Trade Web, comparing the observed values of a number of structural quantities of interest with the expected ones, calculated via our randomization procedure. Interestingly, the behavior of the World Trade Web in this new representation is strongly different from the monopartite analogue, showing highly non-trivial patterns of self-organization.",
    	author = "Saracco, Fabio and {Di Clemente}, Riccardo and Gabrielli, Andrea and Squartini, Tiziano",
    	doi = "10.1038/srep10595",
    	issn = "2045-2322",
    	journal = "Scientific Reports",
    	month = "jun",
    	pages = 10595,
    	pmid = 26029820,
    	title = "{Randomizing bipartite networks: the case of the World Trade Web}",
    	url = "http://arxiv.org/abs/1503.05098{\%}5Cnhttp://www.nature.com/articles/srep10595 http://www.nature.com/articles/srep10595",
    	volume = 5,
    	year = 2015
    }
    
  21. Marco Alberto Javarone and Tiziano Squartini. Conformism-driven phases of opinion formation on heterogeneous networks: the q-voter model case. JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT, October 2015. DOI BibTeX

    @article{ISI:000366633600003,
    	abstract = "The q-voter model, a variant of the classic voter model, has been analyzed by several authors. While allowing us to study opinion dynamics, this model is also believed to be one of the most representative among the many defined in the wide field of sociophysics. Here, we investigate the consequences of conformity on the consensus reaching process, by numerically simulating a q-voter model with agents behaving either as conformists or nonconformists, embedded on heterogeneous network topologies (as small-world and scale-free). In fact, although it is already known that conformity enhances the reaching of consensus, the related process is often studied only on fully-connected networks, thus strongly limiting our full understanding of it. This paper represents a first step in the direction of analyzing more realistic social models, showing that different opinion formation phases, driven by the conformist agents density, are observable. As a result, we identify threshold values of the density of conformist agents, varying across different topologies and separating different regimes of our system, ranging from a disordered phase, where different opinions coexist, to a gradually more ordered phase, where consensus is eventually reached.",
    	author = "Javarone, Marco Alberto and Squartini, Tiziano",
    	doi = "10.1088/1742-5468/2015/10/P10002",
    	issn = "1742-5468",
    	journal = "JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT",
    	month = "oct",
    	title = "{Conformism-driven phases of opinion formation on heterogeneous networks: the q-voter model case}",
    	year = 2015
    }
    
  22. Serge Galam, Marco Alberto Javarone and Tiziano Squartini. SEDNAM - Socio-Economic Dynamics: Networks and Agent-Based Models - Introduction. In LM Aiello and D McFarland (eds.). Social Informatics 8852. 2015, 321–322. DOI BibTeX

    @inproceedings{ISI:000380559900040,
    	annote = "SocInfo International Workshops, Barcelona, SPAIN, NOV 10, 2014",
    	author = "Galam, Serge and Javarone, Marco Alberto and Squartini, Tiziano",
    	booktitle = "Social Informatics",
    	doi = "10.1007/978-3-319-15168-7_40",
    	editor = "{Aiello, LM and McFarland, D}",
    	isbn = "978-3-319-15168-7; 978-3-319-15167-0",
    	issn = "0302-9743",
    	organization = "Microsoft Res; Facebook; Yahoo Labs; Stanford, Ctr Computat Social Sci; Barcelona Media; SocialSensor; IEEE Special Techn Community Social Networking; STC Social Networking",
    	pages = "321--322",
    	series = "Lecture Notes in Computer Science",
    	title = "{SEDNAM - Socio-Economic Dynamics: Networks and Agent-Based Models - Introduction}",
    	volume = 8852,
    	year = 2015
    }
    
  23. Tiziano Squartini, Joey De Mol, Frank Den Hollander and Diego Garlaschelli. Breaking of Ensemble Equivalence in Networks. Physical Review Letters 115(26):1–5, 2015. DOI BibTeX

    @article{Squartini2015,
    	abstract = "It is generally believed that, in the thermodynamic limit, the microcanonical description as a function of energy coincides with the canonical description as a function of temperature. However, various examples of systems for which the microcanonical and canonical ensembles are not equivalent have been identified. A complete theory of this intriguing phenomenon is still missing. Here we show that ensemble nonequivalence can manifest itself also in random graphs with topological constraints. We find that, while graphs with a given number of links are ensemble-equivalent, graphs with a given degree sequence are not. This result holds irrespective of whether the energy is nonadditive (as in unipartite graphs) or additive (as in bipartite graphs). In contrast with previous expectations, our results show that: (1) physically, nonequivalence can be induced by an extensive number of local constraints, and not necessarily by long-range interactions or nonadditivity; (2) mathematically, nonquivalence is determined by a different large-deviation behaviour of microcanonical and canonical probabilities for a single microstate, and not necessarily for almost all microstates. The latter criterion, which is entirely local, is not restricted to networks and holds in general.",
    	archiveprefix = "arXiv",
    	arxivid = "1501.00388",
    	author = "Squartini, Tiziano and {De Mol}, Joey and {Den Hollander}, Frank and Garlaschelli, Diego",
    	doi = "10.1103/PhysRevLett.115.268701",
    	eprint = "1501.00388",
    	file = ":Users/Gcalda/Google Drive (This email address is being protected from spambots. You need JavaScript enabled to view it.)/Mendeley Desktop/Squartini et al/Physical Review Letters/Squartini et al. - 2015 - Breaking of Ensemble Equivalence in Networks.pdf:pdf",
    	issn = 10797114,
    	journal = "Physical Review Letters",
    	number = 26,
    	pages = "1--5",
    	pmid = 26765034,
    	title = "{Breaking of Ensemble Equivalence in Networks}",
    	volume = 115,
    	year = 2015
    }
    
  24. Tiziano Squartini, Enrico Ser-Giacomi, Diego Garlaschelli and George Judge. Information Recovery in Behavioral Networks. Plos One 10(5):e0125077, 2015. URL, DOI BibTeX

    @article{squartini2015information,
    	author = "Squartini, Tiziano and Ser-Giacomi, Enrico and Garlaschelli, Diego and Judge, George",
    	doi = "10.1371/journal.pone.0125077",
    	issn = "1932-6203",
    	journal = "Plos One",
    	number = 5,
    	pages = "e0125077",
    	title = "{Information Recovery in Behavioral Networks}",
    	url = "http://dx.plos.org/10.1371/journal.pone.0125077",
    	volume = 10,
    	year = 2015
    }
    
  25. Tiziano Squartini, Rossana Mastrandrea and Diego Garlaschelli. Unbiased sampling of network ensembles. New J Phys 17(2):23052, 2015. DOI BibTeX

    @article{squartini2015unbiased,
    	abstract = "Sampling random graphs with given properties is a key step in the analysis of networks, as random ensembles represent basic null models required to identify patterns such as communities and motifs. A key requirement is that the sampling process is unbiased and efficient. The main approaches are microcanonical, i.e. they sample graphs that exactly match the enforced constraints. Unfortunately, when applied to strongly heterogeneous networks (including most real-world graphs), the majority of these approaches become biased and/or time-consuming. Moreover, the algorithms defined in the simplest cases (such as binary graphs with given degrees) are not easily generalizable to more complicated ensembles. Here we propose a solution to the problem via the introduction of a `maximize-and-sample' (`Max {\&} Sam') method to correctly sample ensembles of networks where the constraints are `soft' i.e. they are realized as ensemble averages. Being based on exact maximum-entropy distributions, our approach is unbiased by construction, even for strongly heterogeneous networks. It is also more computationally efficient than most microcanonical alternatives. Finally, it works for both binary and weighted networks with a variety of constraints, including combined degree-strengths sequences and full reciprocity structure, for which no alternative method exists. Our method can also be turned into a microcanonical one, via a restriction to the relevant subset. We show various applications to real-world networks and provide a code implementing all our algorithms.",
    	author = "Squartini, Tiziano and Mastrandrea, Rossana and Garlaschelli, Diego",
    	doi = "10.1088/1367-2630/17/2/023052",
    	journal = "New J Phys",
    	keywords = "02.10.Ox,02.70.Rr,05.10.-a,89.75.Hc,complex networks,ensemble nonequivalence,maximum entropy principle,null models of graphs,sampling network ensembles",
    	number = 2,
    	pages = 23052,
    	publisher = "IOP Publishing",
    	title = "{Unbiased sampling of network ensembles}",
    	volume = 17,
    	year = 2015
    }
    
  26. Assaf Almog, Tiziano Squartini and Diego Garlaschelli. A GDP-driven model for the binary and weighted structure of the International Trade Network. New Journal of Physics 17(1):013009, January 2015. URL, DOI BibTeX

    @article{almog2015gdp,
    	author = "Almog, Assaf and Squartini, Tiziano and Garlaschelli, Diego",
    	doi = "10.1088/1367-2630/17/1/013009",
    	file = ":Users/Gcalda/Dropbox (IMT Alti Studi Lucca)/Mendeley Desktop/Almog, Squartini, Garlaschelli/New Journal of Physics/Almog, Squartini, Garlaschelli - 2015 - A GDP-driven model for the binary and weighted structure of the International Trade Network.pdf:pdf",
    	isbn = "doi:10.1088/1367-2630/17/1/013009",
    	issn = "1367-2630",
    	journal = "New Journal of Physics",
    	language = "en",
    	month = "jan",
    	number = 1,
    	pages = 013009,
    	publisher = "IOP Publishing",
    	title = "{A GDP-driven model for the binary and weighted structure of the International Trade Network}",
    	url = "http://iopscience.iop.org/article/10.1088/1367-2630/17/1/013009",
    	volume = 17,
    	year = 2015
    }
    
  27. Rossana Mastrandrea, Julie Fournet and Alain Barrat. Contact patterns in a high school: A comparison between data collected using wearable sensors, contact diaries and friendship surveys. PLoS ONE 10(9):1–26, 2015. DOI BibTeX

    @article{mastrandrea2015contact,
    	abstract = "Given their importance in shaping social networks and determining how information or transmissible diseases propagate in a population, interactions between individuals are the subject of many data collection efforts. To this aim, different methods are commonly used, ranging from diaries and surveys to decentralised infrastructures based on wearable sensors. These methods have each advantages and limitations but are rarely compared in a given setting. Moreover, as surveys targeting friendship relations might suffer less from memory biases than contact diaries, it is interesting to explore how actual contact patterns occurring in day-to-day life compare with friendship relations and with online social links. Here we make progresses in these directions by leveraging data collected in a French high school and concerning (i) face-to-face contacts measured by two concurrent methods, namely wearable sensors and contact diaries, (ii) self-reported friendship surveys, and (iii) online social links. We compare the resulting data sets and find that most short contacts are not reported in diaries while long contacts have a large reporting probability, and that the durations of contacts tend to be overestimated in the diaries. Moreover, measured contacts corresponding to reported friendship can have durations of any length but all long contacts do correspond to a reported friendship. On the contrary, online links that are not also reported in the friendship survey correspond to short face-to-face contacts, highlighting the difference of nature between reported friendships and online links. Diaries and surveys suffer moreover from a low sampling rate, as many students did not fill them, showing that the sensor-based platform had a higher acceptability. We also show that, despite the biases of diaries and surveys, the overall structure of the contact network, as quantified by the mixing patterns between classes, is correctly captured by both networks of self-reported contacts and of friendships, and we investigate the correlations between the number of neighbors of individuals in the three networks. Overall, diaries and surveys tend to yield a correct picture of the global structural organization of the contact network, albeit with much less links, and give access to a sort of backbone of the contact network corresponding to the strongest links, i.e., the contacts of longest cumulative durations.",
    	archiveprefix = "arXiv",
    	arxivid = "1506.03645",
    	author = "Mastrandrea, Rossana and Fournet, Julie and Barrat, Alain",
    	doi = "10.1371/journal.pone.0136497",
    	eprint = "1506.03645",
    	file = ":Users/Gcalda/Google Drive (This email address is being protected from spambots. You need JavaScript enabled to view it.)/Mendeley Desktop/Mastrandrea, Fournet, Barrat/PLoS ONE/Mastrandrea, Fournet, Barrat - 2015 - Contact patterns in a high school A comparison between data collected using wearable sensors, cont.pdf:pdf",
    	isbn = "1932-6203 (Electronic)$\backslash$r1932-6203 (Linking)",
    	issn = 19326203,
    	journal = "PLoS ONE",
    	number = 9,
    	pages = "1--26",
    	pmid = 26325289,
    	title = "{Contact patterns in a high school: A comparison between data collected using wearable sensors, contact diaries and friendship surveys}",
    	volume = 10,
    	year = 2015
    }