Do Diffusion Protocols Govern Cascade Growth?

Large cascades can develop in online social networks as people share information with one another. Though simple reshare cascades have been studied extensively, the full range of cascading behaviors on social media is much more diverse. Here we study how diffusion protocols, or the social exchanges that enable information transmission, affect cascade growth, analogous to the way communication protocols define how information is transmitted from one point to another. Studying 98 of the largest information cascades on Facebook, we find a wide range of diffusion protocols - from cascading reshares of images, which use a simple protocol of tapping a single button for propagation, to the ALS Ice Bucket Challenge, whose diffusion protocol involved individuals creating and posting a video, and then nominating specific others to do the same. We find recurring classes of diffusion protocols, and identify two key counterbalancing factors in the construction of these protocols, with implications for a cascade's growth: the effort required to participate in the cascade, and the social cost of staying on the sidelines. Protocols requiring greater individual effort slow down a cascade's propagation, while those imposing a greater social cost of not participating increase the cascade's adoption likelihood. The predictability of transmission also varies with protocol. But regardless of mechanism, the cascades in our analysis all have a similar reproduction number ($\approx$ 1.8), meaning that lower rates of exposure can be offset with higher per-exposure rates of adoption. Last, we show how a cascade's structure can not only differentiate these protocols, but also be modeled through branching processes. Together, these findings provide a framework for understanding how a wide variety of information cascades can achieve substantial adoption across a network.Comment: ICWSM 201

Computational Social Science

A field is emerging that leverages the capacity to collect and analyze data at a scale that may reveal patterns of individual and group behaviors.Governmen

Structural and Dynamical Patterns on Online Social Networks: the Spanish May 15th Movement as a case study

The number of people using online social networks in their everyday life is continuously growing at a pace never saw before. This new kind of communication has an enormous impact on opinions, cultural trends, information spreading and even in the commercial success of new products. More importantly, social online networks have revealed as a fundamental organizing mechanism in recent country-wide social movements. In this paper, we provide a quantitative analysis of the structural and dynamical patterns emerging from the activity of an online social network around the ongoing May 15th (15M) movement in Spain. Our network is made up by users that exchanged tweets in a time period of one month, which includes the birth and stabilization of the 15M movement. We characterize in depth the growth of such dynamical network and find that it is scale-free with communities at the mesoscale. We also find that its dynamics exhibits typical features of critical systems such as robustness and power-law distributions for several quantities. Remarkably, we report that the patterns characterizing the spreading dynamics are asymmetric, giving rise to a clear distinction between information sources and sinks. Our study represent a first step towards the use of data from online social media to comprehend modern societal dynamics.Comment: 16 pages, 7 figure

In Vitro Selection of a DNA-Templated Small-Molecule Library Reveals a Class of Macrocyclic Kinase Inhibitors

DNA-templated organic synthesis enables the translation of DNA sequences into synthetic small-molecule libraries suitable for in vitro selection. Previously, we described the DNA-templated multistep synthesis of a 13 824-membered small-molecule macrocycle library. Here, we report the discovery of small molecules that modulate the activity of kinase enzymes through the in vitro selection of this DNA-templated small-molecule macrocycle library against 36 biomedically relevant protein targets. DNA encoding selection survivors was amplified by PCR and identified by ultra-high-throughput DNA sequencing. Macrocycles corresponding to DNA sequences enriched upon selection against several protein kinases were synthesized on a multimilligram scale. In vitro assays revealed that these macrocycles inhibit (or activate) the kinases against which they were selected with IC50 values as low as 680 nM. We characterized in depth a family of macrocycles enriched upon selection against Src kinase, and showed that inhibition was highly dependent on the identity of macrocycle building blocks as well as on backbone conformation. Two macrocycles in this family exhibited unusually strong Src inhibition selectivity even among kinases closely related to Src. One macrocycle was found to activate, rather than inhibit, its target kinase, VEGFR2. Taken together, these results establish the use of DNA-templated synthesis and in vitro selection to discover small molecules that modulate enzyme activities, and also reveal a new scaffold for selective ATP-competitive kinase inhibition.Chemistry and Chemical Biolog

Experimental evidence for scale-induced category convergence across populations

Individuals vary widely in how they categorize novel and ambiguous phenomena. This individual variation has led influential theories in cognitive and social science to suggest that communication in large social groups introduces path dependence in category formation, which is expected to lead separate populations toward divergent cultural trajectories. Yet, anthropological data indicates that large, independent societies consistently arrive at highly similar category systems across a range of topics. How is it possible for diverse populations, consisting of individuals with significant variation in how they categorize the world, to independently construct similar category systems? Here, we investigate this puzzle experimentally by creating an online "Grouping Game" in which we observe how people in small and large populations collaboratively construct category systems for a continuum of ambiguous stimuli. We find that solitary individuals and small groups produce highly divergent category systems; however, across independent trials with unique participants, large populations consistently converge on highly similar category systems. A formal model of critical mass dynamics in social networks accurately predicts this process of scale-induced category convergence. Our findings show how large communication networks can filter lexical diversity among individuals to produce replicable society-level patterns, yielding unexpected implications for cultural evolution

Seller activity in a virtual marketplace

As virtual goods continue to proliferate in online worlds, understanding their production, consumption and distribution remains exciting for scholars, technology companies and policy makers alike. We present a descriptive study of the activities of successful sellers in Second Life, a 3D virtual world that allows users to create their content and even to make money by selling it to other users. We combine user log analysis, network analysis and content analysis to examine cycles in trading volume, market segmentation and specialization, geographic concentration and the impact of social capital on economic success, revealing important insights regarding virtual markets, as well as differences between the very top sellers and those making a more modest income.</jats:p

Seller activity in a virtual marketplace

As virtual goods continue to proliferate in online worlds, understanding their production, consumption and distribution remains exciting for scholars, technology companies and policy makers alike. We present a descriptive study of the activities of successful sellers in Second Life, a 3D virtual world that allows users to create their content and even to make money by selling it to other users. We combine user log analysis, network analysis and content analysis to examine cycles in trading volume, market segmentation and specialization, geographic concentration and the impact of social capital on economic success, revealing important insights regarding virtual markets, as well as differences between the very top sellers and those making a more modest income