Measuring Online Social Bubbles

Social media have quickly become a prevalent channel to access information, spread ideas, and influence opinions. However, it has been suggested that social and algorithmic filtering may cause exposure to less diverse points of view, and even foster polarization and misinformation. Here we explore and validate this hypothesis quantitatively for the first time, at the collective and individual levels, by mining three massive datasets of web traffic, search logs, and Twitter posts. Our analysis shows that collectively, people access information from a significantly narrower spectrum of sources through social media and email, compared to search. The significance of this finding for individual exposure is revealed by investigating the relationship between the diversity of information sources experienced by users at the collective and individual level. There is a strong correlation between collective and individual diversity, supporting the notion that when we use social media we find ourselves inside "social bubbles". Our results could lead to a deeper understanding of how technology biases our exposure to new information

Automatic instantiation of abstract tests to specific configurations for large critical control systems

Computer-based control systems have grown in size, complexity, distribution and criticality. In this paper a methodology is presented to perform an ‘abstract testing’ of such large control systems in an efficient way: an abstract test is specified directly from system functional requirements and has to be instantiated in more test runs to cover a specific configuration, comprising any number of control entities (sensors, actuators and logic processes). Such a process is usually performed by hand for each installation of the control system, requiring a considerable time effort and being an error-prone verification activity. To automate a safe passage from abstract tests, related to the so-called generic software application, to any specific installation, an algorithm is provided, starting from a reference architecture and a statebased behavioural model of the control software. The presented approach has been applied to a railway interlocking system, demonstrating its feasibility and effectiveness in several years of testing experience

An exactly solvable model for a beta-hairpin with random interactions

I investigate a disordered version of a simplified model of protein folding, with binary degrees of freedom, applied to an ideal beta-hairpin structure. Disorder is introduced by assuming that the contact energies are independent and identically distributed random variables. The equilibrium free-energy of the model is studied, performing the exact calculation of its quenched value and proving the self-averaging feature.Comment: 9 page

The egalitarian effect of search engines

Search engines have become key media for our scientific, economic, and social activities by enabling people to access information on the Web in spite of its size and complexity. On the down side, search engines bias the traffic of users according to their page-ranking strategies, and some have argued that they create a vicious cycle that amplifies the dominance of established and already popular sites. We show that, contrary to these prior claims and our own intuition, the use of search engines actually has an egalitarian effect. We reconcile theoretical arguments with empirical evidence showing that the combination of retrieval by search engines and search behavior by users mitigates the attraction of popular pages, directing more traffic toward less popular sites, even in comparison to what would be expected from users randomly surfing the Web.Comment: 9 pages, 8 figures, 2 appendices. The final version of this e-print has been published on the Proc. Natl. Acad. Sci. USA 103(34), 12684-12689 (2006), http://www.pnas.org/cgi/content/abstract/103/34/1268

Competition among memes in a world with limited attention

The wide adoption of social media has increased the competition among ideas for our finite attention. We employ a parsimonious agent-based model to study whether such a competition may affect the popularity of different memes, the diversity of information we are exposed to, and the fading of our collective interests for specific topics. Agents share messages on a social network but can only pay attention to a portion of the information they receive. In the emerging dynamics of information diffusion, a few memes go viral while most do not. The predictions of our model are consistent with empirical data from Twitter, a popular microblogging platform. Surprisingly, we can explain the massive heterogeneity in the popularity and persistence of memes as deriving from a combination of the competition for our limited attention and the structure of the social network, without the need to assume different intrinsic values among ideas

Short period attractors and non-ergodic behavior in the deterministic fixed energy sandpile model

We study the asymptotic behaviour of the Bak, Tang, Wiesenfeld sandpile automata as a closed system with fixed energy. We explore the full range of energies characterizing the active phase. The model exhibits strong non-ergodic features by settling into limit-cycles whose period depends on the energy and initial conditions. The asymptotic activity $\rho_a$ (topplings density) shows, as a function of energy density $\zeta$, a devil's staircase behaviour defining a symmetric energy interval-set over which also the period lengths remain constant. The properties of $\zeta$-$\rho_a$ phase diagram can be traced back to the basic symmetries underlying the model's dynamics.Comment: EPL-style, 7 pages, 3 eps figures, revised versio

Friction Interventions to Curb the Spread of Misinformation on Social Media

Social media has enabled the spread of information at unprecedented speeds and scales, and with it the proliferation of high-engagement, low-quality content. *Friction* -- behavioral design measures that make the sharing of content more cumbersome -- might be a way to raise the quality of what is spread online. Here, we study the effects of friction with and without quality-recognition learning. Experiments from an agent-based model suggest that friction alone decreases the number of posts without improving their quality. A small amount of friction combined with learning, however, increases the average quality of posts significantly. Based on this preliminary evidence, we propose a friction intervention with a learning component about the platform's community standards, to be tested via a field experiment. The proposed intervention would have minimal effects on engagement and may easily be deployed at scale

Characterizing and modeling the dynamics of online popularity

Online popularity has enormous impact on opinions, culture, policy, and profits. We provide a quantitative, large scale, temporal analysis of the dynamics of online content popularity in two massive model systems, the Wikipedia and an entire country's Web space. We find that the dynamics of popularity are characterized by bursts, displaying characteristic features of critical systems such as fat-tailed distributions of magnitude and inter-event time. We propose a minimal model combining the classic preferential popularity increase mechanism with the occurrence of random popularity shifts due to exogenous factors. The model recovers the critical features observed in the empirical analysis of the systems analyzed here, highlighting the key factors needed in the description of popularity dynamics.Comment: 5 pages, 4 figures. Modeling part detailed. Final version published in Physical Review Letter

Transfer matrix solution of the Wako-Sait\^o-Mu\~noz-Eaton model augmented by arbitrary short range interactions

The Wako-Sait{\^o}-Mu\~noz-Eaton (WSME) model, initially introduced in the theory of protein folding, has also been used in modeling the RNA folding and some epitaxial phenomena. The advantage of this model is that it admits exact solution in the general inhomogeneous case (Bruscolini and Pelizzola, 2002) which facilitates the study of realistic systems. However, a shortcoming of the model is that it accounts only for interactions within continuous stretches of native bonds or atomic chains while neglecting interstretch (interchain) interactions. But due to the biopolymer (atomic chain) flexibility, the monomers (atoms) separated by several non-native bonds along the sequence can become closely spaced. This produces their strong interaction. The inclusion of non-WSME interactions into the model makes the model more realistic and improves its performance. In this study we add arbitrary interactions of finite range and solve the new model by means of the transfer matrix technique. We can therefore exactly account for the interactions which in proteomics are classified as medium- and moderately long-range ones.Comment: 15 pages, 2 figure