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 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.

Research of the Method for Traffic Generating Based on Genetic Algorithm

2014 ◽  
Vol 701-702 ◽  
pp. 3-7
Author(s):  
Liu Bo
Keyword(s):  
Genetic Algorithm ◽  
Network Traffic ◽  
Large Scale ◽  
Network Reliability ◽  
Actual Usage ◽  
Large Scale Network ◽  
Scale Network ◽  
Self Similar ◽  
Optimal Values

It has great impact on result of the network test or simulation if the test simulated traffic is corresponding to real situation. The network traffic is the superposition of different traffic streams in the actual usage of the network. But because of the complexity and time-consumption to generate different traffic streams, it is difficult to generate the network traffic in the simulation for the large scale network. This paper proposes a kind of method for traffic generating based on genetic algorithm .According to building the self-similar traffic model ,the optimal values of the model’s parameters has been obtained. A case study shows the effectiveness of the method for the network reliability.

scholarly journals Portable neuromodulation induces neuroplasticity to re-activate motor function recovery from brain injury: A high-density MEG case study

2020 ◽  
Author(s):  
Ryan C.N. D'Arcy ◽  
Trevor Greene ◽  
Debbie Greene ◽  
Zack Frehlick ◽  
Shaun D. Fickling ◽  
...  
Keyword(s):  
Brain Injury ◽  
Motor Function ◽  
Large Scale ◽  
Rehabilitation Program ◽  
High Density ◽  
Cortical Activation ◽  
Valuable Insight ◽  
Large Scale Network ◽  
Scale Network

Abstract Background: In a recent high-profile case study, we used functional magnetic resonance imaging (fMRI) to monitor improvements in motor function related to neuroplasticity following rehabilitation for severe traumatic brain injury (TBI). The findings demonstrated that motor function improvements can occur years beyond current established limits. The current study extends the functional imaging investigation to characterize neuromodulation effects on neuroplasticity to further push the limits.Methods: Canadian Soldier Captain (retired) Trevor Greene (TG) survived a severe open-TBI when attacked with an axe during a 2006 combat tour in Afghanistan. TG has since continued intensive daily rehabilitation to recover motor function, experiencing an extended plateau using conventional physical therapy. To overcome this plateau, we paired translingual neurostimulation (TLNS) with the continuing rehabilitation program. Results: Combining TLNS with rehabilitation resulted in demonstrable clinical improvements along with corresponding changes in movement evoked electro-encephalography (EEG) activity. High-density magneto-encephalography (MEG) characterized cortical activation changes in corresponding beta frequency range (27Hz). MEG activation changes corresponded with reduced interhemispheric inhibition in the post-central gyri regions together with increased right superior/middle frontal activation suggesting large scale network level changes. Conclusions: The findings provide valuable insight into the potential importance of non-invasive neuromodulation to enhance neuroplasticity mechanisms for recovery beyond the perceived limits of rehabilitation.

scholarly journals Portable neuromodulation induces neuroplasticity to re-activate motor function recovery from brain injury: A high-density MEG case study

2020 ◽  
Author(s):  
Ryan C.N. D'Arcy ◽  
Trevor Greene ◽  
Debbie Greene ◽  
Zack Frehlick ◽  
Shaun D. Fickling ◽  
...  
Keyword(s):  
Brain Injury ◽  
Motor Function ◽  
Large Scale ◽  
Rehabilitation Program ◽  
High Density ◽  
Cortical Activation ◽  
Valuable Insight ◽  
Large Scale Network ◽  
Scale Network

Abstract Background: In a recent high-profile case study, we used functional magnetic resonance imaging (fMRI) to monitor improvements in motor function related to neuroplasticity following rehabilitation for severe traumatic brain injury (TBI). The findings demonstrated that motor function improvements can occur years beyond current established limits. The current study extends the functional imaging investigation to characterize neuromodulation effects on neuroplasticity to further push the limits.Methods: Canadian Soldier Captain (retired) Trevor Greene (TG) survived a severe open-TBI when attacked with an axe during a 2006 combat tour in Afghanistan. TG has since continued intensive daily rehabilitation to recover motor function, experiencing an extended plateau using conventional physical therapy. To overcome this plateau, we paired translingual neurostimulation (TLNS) with the continuing rehabilitation program.Results: Combining TLNS with rehabilitation resulted in demonstrable clinical improvements along with corresponding changes in movement evoked electro-encephalography (EEG) activity. High-density magneto-encephalography (MEG) characterized cortical activation changes in corresponding beta frequency range (27Hz). MEG activation changes corresponded with reduced interhemispheric inhibition in the post-central gyri regions together with increased right superior/middle frontal activation suggesting large scale network level changes.Conclusions: The findings provide valuable insight into the potential importance of non-invasive neuromodulation to enhance neuroplasticity mechanisms for recovery beyond the perceived limits of rehabilitation.

scholarly journals Portable neuromodulation induces neuroplasticity to re-activate motor function recovery from brain injury: a high-density MEG case study

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Ryan C. N. D’Arcy ◽  
Trevor Greene ◽  
Debbie Greene ◽  
Zack Frehlick ◽  
Shaun D. Fickling ◽  
...  
Keyword(s):  
Brain Injury ◽  
Motor Function ◽  
Large Scale ◽  
Rehabilitation Program ◽  
High Density ◽  
Cortical Activation ◽  
Valuable Insight ◽  
Large Scale Network ◽  
Scale Network

Abstract Background In a recent high-profile case study, we used functional magnetic resonance imaging (fMRI) to monitor improvements in motor function related to neuroplasticity following rehabilitation for severe traumatic brain injury (TBI). The findings demonstrated that motor function improvements can occur years beyond current established limits. The current study extends the functional imaging investigation to characterize neuromodulation effects on neuroplasticity to further push the limits. Methods Canadian Soldier Captain (retired) Trevor Greene (TG) survived a severe open-TBI when attacked with an axe during a 2006 combat tour in Afghanistan. TG has since continued intensive daily rehabilitation to recover motor function, experiencing an extended plateau using conventional physical therapy. To overcome this plateau, we paired translingual neurostimulation (TLNS) with the continuing rehabilitation program. Results Combining TLNS with rehabilitation resulted in demonstrable clinical improvements along with corresponding changes in movement evoked electro-encephalography (EEG) activity. High-density magneto-encephalography (MEG) characterized cortical activation changes in corresponding beta frequency range (27 Hz). MEG activation changes corresponded with reduced interhemispheric inhibition in the post-central gyri regions together with increased right superior/middle frontal activation suggesting large scale network level changes. Conclusions The findings provide valuable insight into the potential importance of non-invasive neuromodulation to enhance neuroplasticity mechanisms for recovery beyond the perceived limits of rehabilitation.

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 Portable neuromodulation induces neuroplasticity to re-activate motor function recovery from brain injury: A high-density MEG case study

2020 ◽  
Author(s):  
Ryan C.N. D'Arcy ◽  
Trevor Greene ◽  
Debbie Greene ◽  
Zack Frehlick ◽  
Shaun D. Fickling ◽  
...  
Keyword(s):  
Brain Injury ◽  
Motor Function ◽  
Large Scale ◽  
Rehabilitation Program ◽  
High Density ◽  
Cortical Activation ◽  
Valuable Insight ◽  
Large Scale Network ◽  
Scale Network

Abstract Background: In a recent high-profile case study, we used functional magnetic resonance imaging (fMRI) to monitor improvements in motor function related to neuroplasticity following rehabilitation for severe traumatic brain injury (TBI). The findings demonstrated that motor function improvements can occur years beyond current established limits. The current study extends the functional imaging investigation to characterize neuromodulation effects on neuroplasticity to further push the limits. Methods: Canadian Soldier Captain (retired) Trevor Greene (TG) survived a severe open-TBI when attacked with an axe during a 2006 combat tour in Afghanistan. TG has since continued intensive daily rehabilitation to recover motor function, experiencing an extended plateau using conventional physical therapy. To overcome this plateau, we paired translingual neurostimulation (TLNS) with the continuing rehabilitation program. Results: Combining TLNS with rehabilitation resulted in demonstrable clinical improvements along with corresponding changes in movement evoked electro-encephalography (EEG) activity. High-density magneto-encephalography (MEG) characterized cortical activation changes in corresponding beta frequency range (27Hz). MEG activation changes corresponded with reduced interhemispheric inhibition in the post-central gyri regions together with increased right superior/middle frontal activation suggesting large scale network level changes. Conclusions: The findings provide valuable insight into the potential importance of non-invasive neuromodulation to enhance neuroplasticity mechanisms for recovery beyond the perceived limits of rehabilitation.

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