scholarly journals From “Nasa Lies” to “Reptilian Eyes”: Mapping Communication About 10 Conspiracy Theories, Their Communities, and Main Propagators on Twitter

2021 ◽  
Vol 7 (2) ◽  
pp. 205630512110174
Author(s):  
Daniela Mahl ◽  
Jing Zeng ◽  
Mike S. Schäfer
Keyword(s):  
Social Media ◽  
Large Scale ◽  
Empirical Support ◽  
User Profiles ◽  
Conspiracy Theories ◽  
Media Companies ◽  
Large Scale Network ◽  
Digital Environments ◽  
Scale Network

In recent years, conspiracy theories have pervaded mainstream discourse. Social media, in particular, reinforce their visibility and propagation. However, most prior studies on the dissemination of conspiracy theories in digital environments have focused on individual cases or conspiracy theories as a generic phenomenon. Our research addresses this gap by comparing the 10 most prominent conspiracy theories on Twitter, the communities supporting them, and their main propagators. Drawing on a dataset of 106,807 tweets published over 6 weeks from 2018 to 2019, we combine large-scale network analysis and in-depth qualitative analysis of user profiles. Our findings illustrate which conspiracy theories are prevalent on Twitter, and how different conspiracy theories are separated or interconnected within communities. In addition, our study provides empirical support for previous assertions that extremist accounts are being “deplatformed” by leading social media companies. We also discuss how the implications of these findings elucidate the role of societal and political contexts in propagating conspiracy theories on social media.

scholarly journals Plasticity of Sensorimotor Networks

2016 ◽  
Vol 23 (2) ◽  
pp. 185-196 ◽  
Author(s):  
Ethan R. Buch ◽  
Sook-Lei Liew ◽  
Leonardo G. Cohen
Keyword(s):  
Motor System ◽  
Degrees Of Freedom ◽  
Large Scale ◽  
System Organization ◽  
Basic Feature ◽  
Intrinsic Variability ◽  
Spatial And Temporal Scales ◽  
Large Scale Network ◽  
Scale Network

Redundancy is an important feature of the motor system, as abundant degrees of freedom are prominent at every level of organization across the central and peripheral nervous systems, and musculoskeletal system. This basic feature results in a system that is both flexible and robust, and which can be sustainably adapted through plasticity mechanisms in response to intrinsic organismal changes and dynamic environments. While much early work of motor system organization has focused on synaptic-based plasticity processes that are driven via experience, recent investigations of neuron–glia interactions, epigenetic mechanisms and large-scale network dynamics have revealed a plethora of plasticity mechanisms that support motor system organization across multiple, overlapping spatial and temporal scales. Furthermore, an important role of these mechanisms is the regulation of intrinsic variability. Here, we review several of these mechanisms and discuss their potential role in neurorehabilitation.

Synchrony of Neuronal Oscillations Controlled by GABAergic Reversal Potentials

2007 ◽  
Vol 19 (3) ◽  
pp. 706-729 ◽  
Author(s):  
Ho Young Jeong ◽  
Boris Gutkin
Keyword(s):  
Large Scale ◽  
Reversal Potential ◽  
Type I ◽  
Gabaergic Synapse ◽  
Neural Oscillators ◽  
Large Scale Network ◽  
Weakly Coupled ◽  
Scale Network ◽  
Large Scale Networks

GABAergic synapse reversal potential is controlled by the concentration of chloride. This concentration can change significantly during development and as a function of neuronal activity. Thus, GABA inhibition can be hyperpolarizing, shunting, or partially depolarizing. Previous results pinpointed the conditions under which hyperpolarizing inhibition (or depolarizing excitation) can lead to synchrony of neural oscillators. Here we examine the role of the GABAergic reversal potential in generation of synchronous oscillations in circuits of neural oscillators. Using weakly coupled oscillator analysis, we show when shunting and partially depolarizing inhibition can produce synchrony, asynchrony, and coexistence of the two. In particular, we show that this depends critically on such factors as the firing rate, the speed of the synapse, spike frequency adaptation, and, most important, the dynamics of spike generation (type I versus type II). We back up our analysis with simulations of small circuits of conductance-based neurons, as well as large-scale networks of neural oscillators. The simulation results are compatible with the analysis: for example, when bistability is predicted analytically, the large-scale network shows clustered states.

scholarly journals Who Says What with Whom: Using Bi-Spectral Clustering to Organize and Analyze Social Media Protest Networks

2020 ◽  
Author(s):  
Kenneth Joseph ◽  
Ryan J. Gallagher ◽  
Brooke Foucault Welles
Keyword(s):  
Social Media ◽  
Spectral Clustering ◽  
Large Scale ◽  
Computational Method ◽  
New Approach ◽  
Large Scale Network ◽  
Long Time ◽  
Communication Context ◽  
Scale Network

Social media protest networks involve many participants, from long-time activists to individuals who are engaged only in a particular protest event. We propose a new approach to studying how various communities of users participate in protest events. Our approach combines two methodological innovations. First, rather than study tweets central to one event, we collect full timelines of user activity leading up to participation in a focal event. Second, we propose bi-spectral clustering as a scalable computational method for rapidly identifying communities of users by the words (hashtags) they use. Using a large sample of tweets from users who discussed the 2016 protests in Charlotte, North Carolina following the extrajudicial killing of Keith Lamont Scott as a case study, we demonstrate how bi-spectral clustering can be applied to sort, sample, and identify ideologically and thematically coherent clusters whose members participated in the protest on Twitter. Our proposed approach provides another tool in the mixed methods scholar’s toolkit to computationally sort and cluster large-scale network data by allowing researchers to look beyond focal hashtags or keywords and situate protest messages within the broader communication context of participating users.

scholarly journals A causal role for pulvinar in coordinating task independent cortico-cortical interactions

2020 ◽  
Author(s):  
Manoj K. Eradath ◽  
Mark A. Pinsk ◽  
Sabine Kastner
Keyword(s):  
Large Scale ◽  
Task Demands ◽  
Causal Role ◽  
Viewing Condition ◽  
Low Frequencies ◽  
Cortical Areas ◽  
Large Scale Network ◽  
Passive Viewing ◽  
Scale Network

AbstractPulvinar is the largest nucleus in the primate thalamus and has topographically organized connections with multiple cortical areas, thereby forming extensive cortico-pulvino-cortical input-output loops. Neurophysiological studies have provided evidence for a role of these transthalamic pathways in regulating information transmission between cortical areas. However, a causal role of pulvinar in regulating cortico-cortical interactions has not yet been demonstrated. In particular, it is not known whether pulvinar’s influences on cortical networks are task-dependent or reflect more basic large-scale network properties that maintain functional connectivity across a network regardless of active task demands. In the current study, under a passive viewing condition, we conducted simultaneous electrophysiological recordings from interconnected ventral (area V4) and dorsal (LIP) nodes of the macaque visual system while reversibly inactivating the dorsal part of lateral pulvinar (dPL), which shares common anatomical connectivity with V4 and LIP. Our goal was to probe a causal role of pulvinar in regulating cortico-cortical interactions in the absence of any active task demands. Our results show a significant reduction in local field potential phase coherence between LIP and V4 in low frequencies (4-15 Hz) following muscimol -a potent GABAA agonist -injection into dPL. At the local level, no significant changes in firing rates or LFP power were observed in LIP or in V4 following dPL inactivation. These results indicate a causal role for pulvinar in synchronizing neural activity between interconnected cortical nodes of a large-scale network, even in the absence of an active task state.Significance StatementPulvinar, the largest nucleus of the primate thalamus, has been implicated in several cognitive functions. The extensive cortico-pulvino-cortical loops formed by pulvinar are suggested to be regulating information transmission between interconnected cortical areas. However, a causal evidence for pulvinar’s role in cortico-cortical interactions in the absence of active task demands is not yet clear. We conducted simultaneous recordings from nodes of macaque visual system (areas V4 and LIP) while inactivating the dorsal part of the lateral pulvinar (dPL) under a passive viewing condition. Our results show a significant reduction in local field phase coherence between LIP and V4 in low frequencies (4-15 Hz) following inactivation of dPL, thus providing evidence for a causal role of pulvinar in regulating cortico-cortical interactions even in the absence of an active task state.

scholarly journals Who Says What with Whom : Using Bi-Spectral Clustering to Organize and Analyze Social Media Protest Networks

2020 ◽  
Vol 2 (2) ◽  
pp. 153-174
Author(s):  
Kenneth Joseph ◽  
Ryan J. Gallagher ◽  
Brooke Foucault Welles
Keyword(s):  
Social Media ◽  
Spectral Clustering ◽  
Large Scale ◽  
Computational Method ◽  
New Approach ◽  
Large Scale Network ◽  
Long Time ◽  
Communication Context ◽  
Scale Network

Abstract Social media protest networks involve many participants, from long-time activists to individuals who are engaged only in a particular protest event. We propose a new approach to studying how various communities of users participate in protest events. Our approach combines two methodological innovations. First, rather than study tweets central to one event, we collect full timelines of user activity leading up to participation in a focal event. Second, we propose bi-spectral clustering as a scalable computational method for rapidly identifying communities of users by the words (hashtags) they use. Using a large sample of tweets from users who discussed the 2016 protests in Charlotte, North Carolina following the extrajudicial killing of Keith Lamont Scott as a case study, we demonstrate how bi-spectral clustering can be applied to sort, sample, and identify ideologically and thematically coherent clusters whose members participated in the protest on Twitter. Our proposed approach provides another tool in the mixed methods scholar’s toolkit to computationally sort and cluster large-scale network data by allowing researchers to look beyond focal hashtags or keywords and situate protest messages within the broader communication context of participating users.

Large-Scale Network Analysis for Online Social Brand Advertising

MIS Quarterly ◽  
2016 ◽  
Vol 40 (4) ◽  
pp. 849-868 ◽  
Author(s):  
Kunpeng Zhang ◽  
◽  
Siddhartha Bhattacharyya ◽  
Sudha Ram ◽  
◽  
...  
Keyword(s):  
Network Analysis ◽  
Large Scale ◽  
Large Scale Network ◽  
Brand Advertising ◽  
Scale Network

A market-based rationale for the privacy paradox

2021 ◽  
pp. 016344372110158
Author(s):  
Opeyemi Akanbi
Keyword(s):  
Social Media ◽  
Market Structures ◽  
Media Companies ◽  
The Social ◽  
Social Media Platforms ◽  
Privacy Paradox ◽  
The Individual ◽  
Privacy Risks ◽  
Social Collective

Moving beyond the current focus on the individual as the unit of analysis in the privacy paradox, this article examines the misalignment between privacy attitudes and online behaviors at the level of society as a collective. I draw on Facebook’s market performance to show how despite concerns about privacy, market structures drive user, advertiser and investor behaviors to continue to reward corporate owners of social media platforms. In this market-oriented analysis, I introduce the metaphor of elasticity to capture the responsiveness of demand for social media to the data (price) charged by social media companies. Overall, this article positions social media as inelastic, relative to privacy costs; highlights the role of the social collective in the privacy crises; and ultimately underscores the need for structural interventions in addressing privacy risks.

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