938 research outputs found
A k-deformed Model of Growing Complex Networks with Fitness
The Barab\'asi-Bianconi (BB) fitness model can be solved by a mapping between
the original network growth model to an idealized bosonic gas. The well-known
transition to Bose-Einstein condensation in the latter then corresponds to the
emergence of "super-hubs" in the network model. Motivated by the preservation
of the scale-free property, thermodynamic stability and self-duality, we
generalize the original extensive mapping of the BB fitness model by using the
nonextensive Kaniadakis k-distribution. Through numerical simulation and
mean-field calculations we show that deviations from extensivity do not
compromise qualitative features of the phase transition. Analysis of the
critical temperature yields a monotonically decreasing dependence on the
nonextensive parameter k
Distance entropy cartography characterises centrality in complex networks
We introduce distance entropy as a measure of homogeneity in the distribution
of path lengths between a given node and its neighbours in a complex network.
Distance entropy defines a new centrality measure whose properties are
investigated for a variety of synthetic network models. By coupling distance
entropy information with closeness centrality, we introduce a network
cartography which allows one to reduce the degeneracy of ranking based on
closeness alone. We apply this methodology to the empirical multiplex lexical
network encoding the linguistic relationships known to English speaking
toddlers. We show that the distance entropy cartography better predicts how
children learn words compared to closeness centrality. Our results highlight
the importance of distance entropy for gaining insights from distance patterns
in complex networks.Comment: 11 page
Influence of augmented humans in online interactions during voting events
The advent of the digital era provided a fertile ground for the development
of virtual societies, complex systems influencing real-world dynamics.
Understanding online human behavior and its relevance beyond the digital
boundaries is still an open challenge. Here we show that online social
interactions during a massive voting event can be used to build an accurate map
of real-world political parties and electoral ranks. We provide evidence that
information flow and collective attention are often driven by a special class
of highly influential users, that we name "augmented humans", who exploit
thousands of automated agents, also known as bots, for enhancing their online
influence. We show that augmented humans generate deep information cascades, to
the same extent of news media and other broadcasters, while they uniformly
infiltrate across the full range of identified groups. Digital augmentation
represents the cyber-physical counterpart of the human desire to acquire power
within social systems.Comment: 11 page
Bots increase exposure to negative and inflammatory content in online social systems
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, bombarding Independentists with violent contents,
increasing their exposure to negative and inflammatory narratives and
exacerbating social conflict online. Our findings stress the importance of
developing countermeasures to unmask these forms of automated social
manipulation.Comment: 8 pages, 5 figure
Forma mentis networks reconstruct how Italian high schoolers and international STEM experts perceive teachers, students, scientists, and school
This study investigates how students and researchers shape their knowledge
and perception of educational topics. The mindset or forma mentis of 159
Italian high school students and of 59 international researchers in STEM are
reconstructed through forma mentis networks, i.e., cognitive networks of
concepts connected by free associations and enriched with sentiment labels. The
layout of conceptual associations between positively/negatively/neutrally
perceived concepts is informative on how people build their own mental
constructs or beliefs about specific topics. Researchers displayed mixed
positive/neutral mental representations of ``teacher'', ``student'' and,
``scientist''. Students' conceptual associations of ``scientist'' were highly
positive and largely non-stereotypical, although links about the ``mad
scientist'' stereotype persisted. Students perceived ``teacher'' as a complex
figure, associated with positive aspects like mentoring/knowledge transmission
but also to negative sides revolving around testing and grading. ``School''
elicited stronger differences between the two groups. In the students' mindset,
``school'' was surrounded by a negative emotional aura or set of associations,
indicating an anxious perception of the school setting, mixing scholastic
concepts, anxiety-eliciting words, STEM disciplines like maths and physics, and
exam-related notions. Researchers' positive stance of ``school'' included
concepts of fun, friendship, and personal growth instead. Along the perspective
of Education Research, the above results are discussed as quantitative evidence
for test- and STEM anxiety co-occurring in the way Italian students perceive
education places and their actors. Detecting these patterns in student
populations through forma mentis networks offers new, simple to gather yet
detailed knowledge for future data-informed intervention policies and action
research.Comment: 12 Pages, 5 Figure
Forma mentis networks map how nursing and engineering students enhance their mindsets about innovation and health during professional growth
Reconstructing a "forma mentis", a mindset, and its changes, means capturing how individuals perceive topics, trends and experiences over time. To this aim we use forma mentis networks (FMNs), which enable direct, microscopic access to how individuals conceptually perceive knowledge and sentiment around a topic, providing richer contextual information than machine learning. FMNs build cognitive representations of stances through psycholinguistic tools like conceptual associations from semantic memory (free associations, i.e., one concept eliciting another) and affect norms (valence, i.e., how attractive a concept is). We test FMNs by investigating how Norwegian nursing and engineering students perceived innovation and health before and after a 2-month research project in e-health. We built and analysed FMNs by six individuals, based on 75 cues about innovation and health, and leading to 1,000 associations between 730 concepts. We repeated this procedure before and after the project. When investigating changes over time, individual FMNs highlighted drastic improvements in all students' stances towards "teamwork", "collaboration", "engineering" and "future", indicating the acquisition and strengthening of a positive belief about innovation. Nursing students improved their perception of "robots" and "technology" and related them to the future of nursing. A group-level analysis related these changes to the emergence, during the project, of conceptual associations about openness towards multidisciplinary collaboration, and a positive, leadershiporiented group dynamics. The whole group identified "mathematics" and "coding" as highly relevant concepts after the project. When investigating persistent associations, characterising the core of students' mindsets, network distance entropy and closeness identified as pivotal in the students' mindsets concepts related to "personal well-being", "professional growth" and "teamwork". This result aligns with and extends previous studies reporting the relevance of teamwork and personal well-being for Norwegian healthcare professionals, also within the novel e-health sector. Our analysis indicates that forma mentis networks are powerful proxies for detecting individual- and grouplevel mindset changes due to professional growth. FMNs open new scenarios for datainformed, multidisciplinary interventions aimed at professional training in innovation.publishedVersio
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