Even with no one in charge, army ants work collectively to build bridges out of their bodies. New research reveals the simple rules that lead to such complex group behavior.

Source: www.quantamagazine.org

In the past weeks, I have received several requests to address the merits of the Anna D. Broido and Aaron Clauset (BC) preprint [1] and their fruitless search for scale-free networks in nature. The preprint’s central claim is deceptively simple: It starts from the textbook definition of a scale-free network as a network with a power law in the degree distribution [2]. It then proceeds to fit a power law to 927 networks, finding that only 4% are scale-free. The author’s conclusion that ‘scale-free networks are rare,’ is turned into the title of the preprint, helping it to get maximal attention. It worked—Quanta magazine accepted its conclusions without reservations. AfterThe Atlantic carried the article, the un-refereed preprint received a degree of media exposure that the original discovery of scale-free networks never enjoyed.

While I saw the conceptual problems with the manuscript, I was convinced that the paper must be technically proficient. Yet, once I did dig into it, it was a real ride. If you have the patience to get to the end of this commentary, you will see where it fails at the conceptual level. But, we will learn that it also fails, repeatedly, at the technical level.

 

Love is All You Need
Clauset’s fruitless search for scale-free networks

Albert-László Barabási

Source: www.barabasilab.com

Societies are complex systems which tend to polarize into sub-groups of individuals with dramatically opposite perspectives. This phenomenon is reflected — and often amplified — in online social networks where, however, humans are no more the only players, and co-exist alongside with social bots, i.e. software-controlled accounts. Analyzing large-scale social data collected during the Catalan referendum for independence on October 1 2017, consisting of nearly 4 millions Twitter posts generated by almost 1 million users, we identify the two polarized groups of Independentists and Constitutionalists and quantify the structural and emotional roles played by social bots. We show that bots act from peripheral areas of the social system to target influential humans of both groups, mostly bombarding Independentists with negative and violent contents, sustaining and inflating instability in this online society. These results quantify the potential dangerous influence of political bots during voting processes.

 

Bots sustain and inflate striking opposition in online social systems
Massimo Stella, Emilio Ferrara, Manlio De Domenico

Source: arxiv.org

After many decades of flourishing computer science it is now rather evident that in a world dominated by different kinds of digital information, both applications and people are forced to seek new, innovative structures and forms of data management and organization. Following this blunt observation, researchers in informatics have strived over the recent years to tackle the non-unique and rather evolving notion of context, which aids significantly the data disambiguation process. Motivated by this environment, this work attempts to summarize and organize in a researcher-friendly tabular manner important or pioneer related research works deriving from diverse computational intelligence domains: Initially, we discuss the influence of context with respect to traditional low-level multimedia content analysis and search, and retrieval tasks and then we advance to the fields of overall computational context-awareness and the so-called human-generated contextual elements. In an effort to provide meaningful information to fellow researchers, this brief survey focuses on the impact of context in modern and popular computing undertakings of our era. More specifically, we focus to the presentation of a short review of visual context modeling methods, followed by the depiction of context-awareness in modern computing. Works dealing with the interpretation of context by human-generated interactions are also discussed herein, as the particular domain gains an ever-increasing proportion of related research nowadays. We then conclude the paper by providing a short discussion on (i) the motivation behind the included context type categorization into three main pillars; (ii) the findings and conclusions of the survey for each context category; and (iii) a couple of brief advices derived from the survey for both interested developers and fellow researchers.

 

The Evolution of Contextual Information Processing in Informatics
Phivos Mylonas

Information 2018, 9(3), 47; doi:10.3390/info9030047

Source: www.mdpi.com

An important way to resolve games of conflict (snowdrift, hawk–dove, chicken) involves adopting a convention: a correlated equilibrium that avoids any conflict between aggressive strategies. Dynamic networks allow individuals to resolve conflict via their network connections rather than changing their strategy. Exploring how behavioral strategies coevolve with social networks reveals new dynamics that can help explain the origins and robustness of conventions. Here, we model the emergence of conventions as correlated equilibria in dynamic networks. Our results show that networks have the tendency to break the symmetry between the two conventional solutions in a strongly biased way. Rather than the correlated equilibrium associated with ownership norms (play aggressive at home, not away), we usually see the opposite host–guest norm (play aggressive away, not at home) evolve on dynamic networks, a phenomenon common to human interaction. We also show that learning to avoid conflict can produce realistic network structures in a way different than preferential attachment models.

Paper on journal website: http://rsif.royalsocietypublishing.org/content/15/140/20170835

Interactive visualization: here