SlideShare uma empresa Scribd logo
1 de 33
Contents




      Tokyo City University   Systems Information Engineering   2
Research Background ~Consumer Side~




                              Figure 1: Changes in the users of SM in Japan (10 - 11)




      Tokyo City University          Systems Information Engineering                    3
Research Background ~Company side~




      Tokyo City University   Systems Information Engineering   4
Purpose of this Research




      Tokyo City University   Systems Information Engineering   5
Result of Analysis ~Similarity of SM
~




       Tokyo City University   Systems Information Engineering   6
Labeling the SM Types




      Tokyo City University   Systems Information Engineering   7
Behavior of the Recipient Information




      Tokyo City University   Systems Information Engineering   8
Behavior of the Recipient Information




      Tokyo City University   Systems Information Engineering   9
Analysis of the Facebook pages




       Tokyo City University   Systems Information Engineering   10
Set the Probability Hierarchy
Transition




      Tokyo City University   Systems Information Engineering   11
Set the Probability Hierarchy
Transition




      Tokyo City University   Systems Information Engineering   12
Set the Probability Hierarchy
Transition




      Tokyo City University   Systems Information Engineering   13
Set the Probability Hierarchy
Transition




      Tokyo City University   Systems Information Engineering   14
Set the Probability Hierarchy
Transition




      Tokyo City University   Systems Information Engineering   15
Statistical Test about Linguistic &
Nonlinguistic Info




        Tokyo City University   Systems Information Engineering   16
Extraction of Keywords prompting
behavior




       Tokyo City University   Systems Information Engineering   17
Assumption Output ~Using SEM analysis~




       Tokyo City University   Systems Information Engineering   18
Conclusion




      Tokyo City University   Systems Information Engineering   19
Future tasks




      Tokyo City University   Systems Information Engineering   20
References




      Tokyo City University   Systems Information Engineering   21
Questions & Answers

  I’m happy to answer your questions!




       Tokyo City University   Systems Information Engineering   22
Definition about the SM and SNS




      Tokyo City University   Systems Information Engineering   23
Definition about the VIRAL & Ex.



                                                                      Empathy!
                                        Diffusion


                                                                        Buy!!



Case Study

1. Spreading of BAD Rumors at the time of the Earthquake
2. Obituary of bin Laden

                Tokyo City University          Systems Information Engineering   24
Companies Purposes of the SM




      Tokyo City University   Systems Information Engineering   25
Changes of the SNS by the trend




      Tokyo City University   Systems Information Engineering   26
Variation in the number of samples




      Tokyo City University   Systems Information Engineering   27
Details of the Probability Transition
Hierarchy




       Tokyo City University   Systems Information Engineering   28
Concrete data used in correspondence
analysis




       Tokyo City University   Systems Information Engineering   29
Result of Morphological Analysis




       Tokyo City University   Systems Information Engineering   30
Assumption Output ~ Concern about Ties ~




       Tokyo City University   Systems Information Engineering   31
Novelty & Usefulness of Research




      Tokyo City University   Systems Information Engineering   32
About Morphological Analysis




      Tokyo City University   Systems Information Engineering   33

Mais conteúdo relacionado

Semelhante a The proposal of the viral model of information which is considering social media interactivity

Social Computing: From Social Informatics to Social Intelligence
Social Computing: From Social Informatics to Social IntelligenceSocial Computing: From Social Informatics to Social Intelligence
Social Computing: From Social Informatics to Social Intelligence
Teklu_U
 

Semelhante a The proposal of the viral model of information which is considering social media interactivity (20)

Social Computing: From Social Informatics to Social Intelligence
Social Computing: From Social Informatics to Social IntelligenceSocial Computing: From Social Informatics to Social Intelligence
Social Computing: From Social Informatics to Social Intelligence
 
Cyber Physical Systems – Collaborating Systems of Systems
Cyber Physical Systems – Collaborating Systems of SystemsCyber Physical Systems – Collaborating Systems of Systems
Cyber Physical Systems – Collaborating Systems of Systems
 
The road to internet of things :a survey
The road to internet of things :a surveyThe road to internet of things :a survey
The road to internet of things :a survey
 
Testing with Fewer Resources: Toward Adaptive Approaches for Cost-effective ...
Testing with Fewer Resources:  Toward Adaptive Approaches for Cost-effective ...Testing with Fewer Resources:  Toward Adaptive Approaches for Cost-effective ...
Testing with Fewer Resources: Toward Adaptive Approaches for Cost-effective ...
 
Testing with Fewer Resources: Toward Adaptive Approaches for Cost-effective ...
Testing with Fewer Resources:  Toward Adaptive Approaches for Cost-effective ...Testing with Fewer Resources:  Toward Adaptive Approaches for Cost-effective ...
Testing with Fewer Resources: Toward Adaptive Approaches for Cost-effective ...
 
Smart Cities: How are they different?
Smart Cities: How are they different? Smart Cities: How are they different?
Smart Cities: How are they different?
 
Internet of Things for Underground Drainage and manhole Monitoring System for...
Internet of Things for Underground Drainage and manhole Monitoring System for...Internet of Things for Underground Drainage and manhole Monitoring System for...
Internet of Things for Underground Drainage and manhole Monitoring System for...
 
Machine Learning for Chemistry: Representing and Intervening
Machine Learning for Chemistry: Representing and InterveningMachine Learning for Chemistry: Representing and Intervening
Machine Learning for Chemistry: Representing and Intervening
 
2012: Natural Computing - The Grand Challenges and Two Case Studies
2012: Natural Computing - The Grand Challenges and Two Case Studies2012: Natural Computing - The Grand Challenges and Two Case Studies
2012: Natural Computing - The Grand Challenges and Two Case Studies
 
A review of IoT-based smart waste level monitoring system for smart cities
A review of IoT-based smart waste level monitoring system for smart citiesA review of IoT-based smart waste level monitoring system for smart cities
A review of IoT-based smart waste level monitoring system for smart cities
 
Profiling Linked Open Data
Profiling Linked Open DataProfiling Linked Open Data
Profiling Linked Open Data
 
IoT and Crime Prevention
IoT and Crime PreventionIoT and Crime Prevention
IoT and Crime Prevention
 
Artificial intelligence in civil engineering seminar report
Artificial intelligence in civil engineering seminar reportArtificial intelligence in civil engineering seminar report
Artificial intelligence in civil engineering seminar report
 
Artificial intelligence in cyber physical systems
Artificial intelligence in cyber physical systemsArtificial intelligence in cyber physical systems
Artificial intelligence in cyber physical systems
 
Overview Of Wcu Research (16 Dec2009)Sj
Overview Of Wcu Research (16 Dec2009)SjOverview Of Wcu Research (16 Dec2009)Sj
Overview Of Wcu Research (16 Dec2009)Sj
 
PWC: Data Driven Cities [2016]
PWC: Data Driven Cities [2016]PWC: Data Driven Cities [2016]
PWC: Data Driven Cities [2016]
 
Data Wrangling Week 4
Data Wrangling Week 4Data Wrangling Week 4
Data Wrangling Week 4
 
The SESERV Project: supporting the Future Internet Socio Economics Community
The SESERV Project: supporting the Future Internet Socio Economics CommunityThe SESERV Project: supporting the Future Internet Socio Economics Community
The SESERV Project: supporting the Future Internet Socio Economics Community
 
What makes smart cities “Smart”?
What makes smart cities “Smart”? What makes smart cities “Smart”?
What makes smart cities “Smart”?
 
What iscs
What iscsWhat iscs
What iscs
 

Último

Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
WSO2
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 

Último (20)

Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, AdobeApidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Spring Boot vs Quarkus the ultimate battle - DevoxxUK
Spring Boot vs Quarkus the ultimate battle - DevoxxUKSpring Boot vs Quarkus the ultimate battle - DevoxxUK
Spring Boot vs Quarkus the ultimate battle - DevoxxUK
 
AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024AXA XL - Insurer Innovation Award Americas 2024
AXA XL - Insurer Innovation Award Americas 2024
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 

The proposal of the viral model of information which is considering social media interactivity

  • 1.
  • 2. Contents Tokyo City University Systems Information Engineering 2
  • 3. Research Background ~Consumer Side~ Figure 1: Changes in the users of SM in Japan (10 - 11) Tokyo City University Systems Information Engineering 3
  • 4. Research Background ~Company side~ Tokyo City University Systems Information Engineering 4
  • 5. Purpose of this Research Tokyo City University Systems Information Engineering 5
  • 6. Result of Analysis ~Similarity of SM ~ Tokyo City University Systems Information Engineering 6
  • 7. Labeling the SM Types Tokyo City University Systems Information Engineering 7
  • 8. Behavior of the Recipient Information Tokyo City University Systems Information Engineering 8
  • 9. Behavior of the Recipient Information Tokyo City University Systems Information Engineering 9
  • 10. Analysis of the Facebook pages Tokyo City University Systems Information Engineering 10
  • 11. Set the Probability Hierarchy Transition Tokyo City University Systems Information Engineering 11
  • 12. Set the Probability Hierarchy Transition Tokyo City University Systems Information Engineering 12
  • 13. Set the Probability Hierarchy Transition Tokyo City University Systems Information Engineering 13
  • 14. Set the Probability Hierarchy Transition Tokyo City University Systems Information Engineering 14
  • 15. Set the Probability Hierarchy Transition Tokyo City University Systems Information Engineering 15
  • 16. Statistical Test about Linguistic & Nonlinguistic Info Tokyo City University Systems Information Engineering 16
  • 17. Extraction of Keywords prompting behavior Tokyo City University Systems Information Engineering 17
  • 18. Assumption Output ~Using SEM analysis~ Tokyo City University Systems Information Engineering 18
  • 19. Conclusion Tokyo City University Systems Information Engineering 19
  • 20. Future tasks Tokyo City University Systems Information Engineering 20
  • 21. References Tokyo City University Systems Information Engineering 21
  • 22. Questions & Answers I’m happy to answer your questions! Tokyo City University Systems Information Engineering 22
  • 23. Definition about the SM and SNS Tokyo City University Systems Information Engineering 23
  • 24. Definition about the VIRAL & Ex. Empathy! Diffusion Buy!! Case Study 1. Spreading of BAD Rumors at the time of the Earthquake 2. Obituary of bin Laden Tokyo City University Systems Information Engineering 24
  • 25. Companies Purposes of the SM Tokyo City University Systems Information Engineering 25
  • 26. Changes of the SNS by the trend Tokyo City University Systems Information Engineering 26
  • 27. Variation in the number of samples Tokyo City University Systems Information Engineering 27
  • 28. Details of the Probability Transition Hierarchy Tokyo City University Systems Information Engineering 28
  • 29. Concrete data used in correspondence analysis Tokyo City University Systems Information Engineering 29
  • 30. Result of Morphological Analysis Tokyo City University Systems Information Engineering 30
  • 31. Assumption Output ~ Concern about Ties ~ Tokyo City University Systems Information Engineering 31
  • 32. Novelty & Usefulness of Research Tokyo City University Systems Information Engineering 32
  • 33. About Morphological Analysis Tokyo City University Systems Information Engineering 33