Our papers are the official record of our discoveries. They allow others to build on and apply our work. Each paper is the result of many months of research, so we make a special effort to make them clear, beautiful and inspirational, and publish them in leading journals.

  • Distress propagation in complex networks: the case of non-linear DebtRank

    MBM. BardosciaFCJPGVGCG. Caldarelli PLoS ONE

    Non-linear distress propagation

    Non-linear models of distress propagation in financial networks characterise key regimes where shocks are either amplified or suppressed.

  • Coupling news sentiment with web browsing data improves prediction of intra-day price dynamics


    News sentiment and price dynamics

    News sentiment analysis and web browsing data are unilluminating alone, but inspected together, predict fluctuations in stock prices.

  • The effects of Twitter sentiment on stock price returns

    GRDAGCG. CaldarelliMGIM PLoS ONE

    Effect of Twitter on stock prices

    When the number of tweets about an event peaks, the sentiment of those tweets correlates strongly with abnormal stock market returns.

  • Using networks to understand medical data: the case of class III malocclusions

    ASA. ScalaPAMSGCG. CaldarelliJMLF PLoS ONE

    Networks for medical data

    Network analysis of diagnostic data identifies combinations of the key factors which cause Class III malocclusion and how they evolve over time.

  • PLoS ONE

    Search queries predict stocks

    Analysis of web search queries about a given stock, from the seemingly uncoordinated activity of many users, can anticipate the trading peak.