Transparency in Social Media : Tools, Methods and Algorithms for Mediating Online Interactions /
Transparency in Social Media : Tools, Methods and Algorithms for Mediating Online Interactions /
- Cham : Springer, 2015.
- vi, 318 pages : ill.:
Contents
Part I: Overtures to Transparency in Social Media
Introduction
References
Socio-Computational Frameworks, Tools and Algorithms for Supporting Transparent Authorship in Social
1 Introduction
2 Models and Methods for Measuring, Analyzing and Influencing Social Interaction, Functional Roles,
3 Exploring Structure and Dynamics of Networks with Social Network Analysis
4 Crowdsourcing for Education, Creative Production, News and Misinformation
4.1 In Sum
4.2 About
Part II: Assessing Provenance and Pathways in Social Media: Case Studies, Methods, and Tools
Robust Aggregation of Inconsistent Information: Concepts and Research Directions
1 Introduction
2 Provenance-Based Data Trustworthiness Assessment
2.1 Background Notions
2.2 Cyclic Trust Computation Framework
2.3 Experimental Evaluation
2.4 Summary
3 IF Algorithms of Laureti et al. and De Kerchove et al.
4 Collusion Attacks
5 Data Aggregation with Protection from Collusions
6 Research Roadmap
References
Weaponized Crowdsourcing: An Emerging Threat and Potential Countermeasures
1 Introduction
2 Background
3 Weaponized Crowdsourcing: An Investigation
3.1 Datasets Collected from Crowdsourcing Sites
3.2 Market Size of Weaponized Crowdsourcing
3.3 Types of Campaigns
3.4 Countries of Requesters and Workers
4 Preventive Approaches
4.1 Automatic Crowdturfing Task Detection
4.2 Tracking Manipulated Content and Detecting Workers in Social Media
4.3 Crowdsourced Mitigation
4.4 Discussion
5 Conclusion
References
The Structures of Twitter Crowds and Conversations
1 Summary of Findings
2 Twitter Social Media Networks
3 Influencers: Hubs and Bridges in Networks
4 A Taxonomy of Network Types: Purpose, Division, Density
5 Part 1: Research Method and Strategy
6 Taking ``Aerial Photographs´´ of Twitter Crowds
7 Group Density
8 More on Hubs and Bridge
9 Part 2: Extracting the Six Conversation and Group Network Structures in Twitter
10 Group Type 1: Polarized
11 Group Type 2: In-Group
In-Group Community Conversation
12 Group Type 3: Brands, Breaking News, and Big Events
13 Group Type 4: Clustered Community
14 Group Type 5: Broadcast
15 Group Type 5: Support
16 Conclusions
Resources
Visible Effort: Visualizing and Measuring Group Structuration Through Social Entropy
1 Introduction
2 CMC and Uneven Online Interaction
3 Measuring Collaborative Unevenness
3.1 Shannon´s Entropy Theory
3.2 Social Entropy Theory
4 Entropy: A Higher Level Structural Indicator
5 Visible Effort: A Technology for Moderating Wiki Collaboration
6 Use Scenario
7 Aligning the Conceptual with the Actual
8 Significance
References
Stepwise Segmented Regression Analysis: An Iterative Statistical Algorithm to Detect and Quantify Ev
1 Data Organization
2 Methodological Objectives
3 Limitations of Existing Methodologies
4 Stepwise Segmented Regression
4.1 Underlying Philosophy
4.2 Procedure
4.3 Step-by-Step Example
5 Discussion
5.1 Heteroscedasticity and Robustness
5.2 Extensibility
6 Conclusions
References
Towards Bottom-Up Decision Making and Collaborative Knowledge Generation in Urban Infrastructure Pro
1 Business of Knowledge and Modern Infrastructure Industry
1.1 Role of Web 2.0 in Public Involvement
1.2 Era of Prosumers
1.3 Prosumerism in Infrastructure Industry
2 Attempts and Shortcomings
3 From Big Data to Knowledge
3.1 IDN as Network of People
3.2 IDN as Network of Ideas
4 Project Discussion Profile
5 Concluding Remarks
References
Biometric-Based User Authentication and Activity Level Detection in a Collaborative Environment
1 Introduction
2 Related Work
3 Proposed Multi-Modal System
3.1 Multi-Modal Sensing
3.2 Individual Identification and Tracking
3.2.1 Gait Recognition
3.2.2 Face Recognition
3.2.3 Speaker Recognition
3.2.4 Match Score Level Fusion
3.3 Activity Recognition
3.3.1 Individual Activity Recognition
3.3.2 Group Activity Recognition
3.4 Individual Contribution Analysis
4 Concluding Remarks
References
Part III: Improving Transparency Through Documentation and Curation
In the Flow: Evolving from Utility Based Social Medium to Community Peer
1 Introduction
2 Design for Utility or Design for Social?
3 nanoHUB
4 Workflows Facilitated by nanoHUB
4.1 Tool Dissemination
4.2 Interface Construction, Interface Maintenance, and Sense-Making
4.3 Augmentative Information and Content Repurposing
5 A Platform for Sociotechnical Research
6 Beyond Social Media Platforms: The Evolution of the Community Peer
References
Ostinato: The Exploration-Automation Cycle of User-Centric, Process-Automated Data-Driven Visual Net
1 Introduction
2 Previous Work
3 Methodology
3.1 Context
3.2 Design Science Research
3.3 Experimental Cases
4 Ostinato Model
4.1 Process Requirements
4.2 Process Model
4.2.1 Phase 1: Data Collection and Refinement
Entity Index Creation
Web/API Crawling
Scraping
Data Aggregation
4.2.2 Phase 2: Network Construction and Analysis
Filtering in Entities
Node and Edge Creation
Metrics Calculation
Nodes and Edge Filtering
Entity Index Refinement
Layout Processing
Visual Properties Configuration
Visualization Provision
Sensemaking, Storytelling and Dashboard Design
5 Discussion
6 Summary
References
Visual Analytics of User Influence and Location-Based Social Networks
1 Introduction
2 Related Work
2.1 Visualization of Social Networks
2.2 Location-Based Social Networks Analysis
3 User Influence-Based Dynamic Social Networks
3.1 Explicit Connections: Replies and Retweets
3.2 Visualization of Dynamic Networks
3.3 Interaction Design
4 Visualization of Location-Based Social Networks for Abnormal Event Detection
4.1 Topic Extraction
4.2 Abnormality Estimation
5 Case Study
6 Conclusion
References
Transparency, Control, and Content Generation on Wikipedia: Editorial Strategies and Technical Affor
1 Introduction
2 History of Interface Changes
3 Standalone Visualizations
4 Article-Level Inequalities
5 Article-Level Visualizations
6 Why Visualizations Haven´t Been Accepted
7 Possible Solutions
References
Part IV: Transparency in Social Media: Ethical and Critical Dimensions
Truth Telling and Deception in the Internet Society
1 Truth or Consequences
2 The Principle of Witness
3 Evasion Tactics
4 Robots Have Limitations
5 Using Computers Correctly
6 Institutions Are Essential
7 An Experimental Test
8 Some Important Metrics
9 New Institutions of Speech
References
Embedding Privacy and Ethical Values in Big Data Technology
1 Introduction
2 Defining Big Data
3 Ethical Issues in the Use of Big Data
3.1 Defining Privacy
3.2 Four Normative Principles as Basis for the Ethical Analysis of Privacy
3.3 Remarks and Explanations
3.4 Contexts of Privacy
4 The Privacy Matrix: How to Think About Privacy in Big Data
4.1 Profiling Individuals with Big Data
4.2 Anonymity, Manipulation and User Consent in Online Communities
4.3 Protecting Vulnerable Populations in Educational Contexts
4.4 Unequal Access to Big Data in Scientific Research
4.5 Big Data and Government Surveillance
4.6 Sale of Big Data in Commercial Contexts
5 Embedding Values in Big Data Technology
5.1 Values Guide the Use of Big Data Technology
5.2 Big Data Tools Enable Realization of Values
5.3 Basing Big Data Tool Design on Target Values
6 Conclusion
References
Critical Thinking and Socio-Technical Methods for Ascertaining Credibility Online
1 Introduction
2 Online Interaction, Virtual Community: The Promises of the Internet Revolution
3 Trust, Credibility, Equality? Understanding the Social Processes That Define Content Production an
Transparency in Social Media
Tools, Methods and Algorithms for Mediating Online Interactions
The volume presents, in a synergistic manner, significant theoretical and practical contributions in the area of social media reputation and authorship measurement, visualization, and modeling. The book justifies and proposes contributions to a future agenda for understanding the requirements for making social media authorship more transparent. Building on work presented in a previous volume of this series, Roles, Trust, and Reputation in Social Media Knowledge Markets, this book discusses new tools, applications, services, and algorithms that are needed for authoring content in a real-time publishing world. These insights may help people who interact and create content through social media better assess their potential for knowledge creation. They may also assist in analyzing audience attitudes, perceptions, and behavior in informal social media or in formal organizational structures. In addition, the volume includes several chapters that analyze the higher order ethical, critical thinking, and philosophical principles that may be used to ground social media authorship. Together, the perspectives presented in this volume help us understand how social media content is created and how its impact can be evaluated. The chapters demonstrate thought leadership through new ways of constructing social media experiences and making traces of social interaction visible. Transparency in Social Media aims to help researchers and practitioners design services, tools, or methods of analysis that encourage a more transparent process of interaction and communication on social media. Knowing who has added what content and with what authority to a specific online social media project can help the user community better understand, evaluate and make decisions and, ultimately, act on the basis of such information.
9783319185514
302.231 / MAT
Contents
Part I: Overtures to Transparency in Social Media
Introduction
References
Socio-Computational Frameworks, Tools and Algorithms for Supporting Transparent Authorship in Social
1 Introduction
2 Models and Methods for Measuring, Analyzing and Influencing Social Interaction, Functional Roles,
3 Exploring Structure and Dynamics of Networks with Social Network Analysis
4 Crowdsourcing for Education, Creative Production, News and Misinformation
4.1 In Sum
4.2 About
Part II: Assessing Provenance and Pathways in Social Media: Case Studies, Methods, and Tools
Robust Aggregation of Inconsistent Information: Concepts and Research Directions
1 Introduction
2 Provenance-Based Data Trustworthiness Assessment
2.1 Background Notions
2.2 Cyclic Trust Computation Framework
2.3 Experimental Evaluation
2.4 Summary
3 IF Algorithms of Laureti et al. and De Kerchove et al.
4 Collusion Attacks
5 Data Aggregation with Protection from Collusions
6 Research Roadmap
References
Weaponized Crowdsourcing: An Emerging Threat and Potential Countermeasures
1 Introduction
2 Background
3 Weaponized Crowdsourcing: An Investigation
3.1 Datasets Collected from Crowdsourcing Sites
3.2 Market Size of Weaponized Crowdsourcing
3.3 Types of Campaigns
3.4 Countries of Requesters and Workers
4 Preventive Approaches
4.1 Automatic Crowdturfing Task Detection
4.2 Tracking Manipulated Content and Detecting Workers in Social Media
4.3 Crowdsourced Mitigation
4.4 Discussion
5 Conclusion
References
The Structures of Twitter Crowds and Conversations
1 Summary of Findings
2 Twitter Social Media Networks
3 Influencers: Hubs and Bridges in Networks
4 A Taxonomy of Network Types: Purpose, Division, Density
5 Part 1: Research Method and Strategy
6 Taking ``Aerial Photographs´´ of Twitter Crowds
7 Group Density
8 More on Hubs and Bridge
9 Part 2: Extracting the Six Conversation and Group Network Structures in Twitter
10 Group Type 1: Polarized
11 Group Type 2: In-Group
In-Group Community Conversation
12 Group Type 3: Brands, Breaking News, and Big Events
13 Group Type 4: Clustered Community
14 Group Type 5: Broadcast
15 Group Type 5: Support
16 Conclusions
Resources
Visible Effort: Visualizing and Measuring Group Structuration Through Social Entropy
1 Introduction
2 CMC and Uneven Online Interaction
3 Measuring Collaborative Unevenness
3.1 Shannon´s Entropy Theory
3.2 Social Entropy Theory
4 Entropy: A Higher Level Structural Indicator
5 Visible Effort: A Technology for Moderating Wiki Collaboration
6 Use Scenario
7 Aligning the Conceptual with the Actual
8 Significance
References
Stepwise Segmented Regression Analysis: An Iterative Statistical Algorithm to Detect and Quantify Ev
1 Data Organization
2 Methodological Objectives
3 Limitations of Existing Methodologies
4 Stepwise Segmented Regression
4.1 Underlying Philosophy
4.2 Procedure
4.3 Step-by-Step Example
5 Discussion
5.1 Heteroscedasticity and Robustness
5.2 Extensibility
6 Conclusions
References
Towards Bottom-Up Decision Making and Collaborative Knowledge Generation in Urban Infrastructure Pro
1 Business of Knowledge and Modern Infrastructure Industry
1.1 Role of Web 2.0 in Public Involvement
1.2 Era of Prosumers
1.3 Prosumerism in Infrastructure Industry
2 Attempts and Shortcomings
3 From Big Data to Knowledge
3.1 IDN as Network of People
3.2 IDN as Network of Ideas
4 Project Discussion Profile
5 Concluding Remarks
References
Biometric-Based User Authentication and Activity Level Detection in a Collaborative Environment
1 Introduction
2 Related Work
3 Proposed Multi-Modal System
3.1 Multi-Modal Sensing
3.2 Individual Identification and Tracking
3.2.1 Gait Recognition
3.2.2 Face Recognition
3.2.3 Speaker Recognition
3.2.4 Match Score Level Fusion
3.3 Activity Recognition
3.3.1 Individual Activity Recognition
3.3.2 Group Activity Recognition
3.4 Individual Contribution Analysis
4 Concluding Remarks
References
Part III: Improving Transparency Through Documentation and Curation
In the Flow: Evolving from Utility Based Social Medium to Community Peer
1 Introduction
2 Design for Utility or Design for Social?
3 nanoHUB
4 Workflows Facilitated by nanoHUB
4.1 Tool Dissemination
4.2 Interface Construction, Interface Maintenance, and Sense-Making
4.3 Augmentative Information and Content Repurposing
5 A Platform for Sociotechnical Research
6 Beyond Social Media Platforms: The Evolution of the Community Peer
References
Ostinato: The Exploration-Automation Cycle of User-Centric, Process-Automated Data-Driven Visual Net
1 Introduction
2 Previous Work
3 Methodology
3.1 Context
3.2 Design Science Research
3.3 Experimental Cases
4 Ostinato Model
4.1 Process Requirements
4.2 Process Model
4.2.1 Phase 1: Data Collection and Refinement
Entity Index Creation
Web/API Crawling
Scraping
Data Aggregation
4.2.2 Phase 2: Network Construction and Analysis
Filtering in Entities
Node and Edge Creation
Metrics Calculation
Nodes and Edge Filtering
Entity Index Refinement
Layout Processing
Visual Properties Configuration
Visualization Provision
Sensemaking, Storytelling and Dashboard Design
5 Discussion
6 Summary
References
Visual Analytics of User Influence and Location-Based Social Networks
1 Introduction
2 Related Work
2.1 Visualization of Social Networks
2.2 Location-Based Social Networks Analysis
3 User Influence-Based Dynamic Social Networks
3.1 Explicit Connections: Replies and Retweets
3.2 Visualization of Dynamic Networks
3.3 Interaction Design
4 Visualization of Location-Based Social Networks for Abnormal Event Detection
4.1 Topic Extraction
4.2 Abnormality Estimation
5 Case Study
6 Conclusion
References
Transparency, Control, and Content Generation on Wikipedia: Editorial Strategies and Technical Affor
1 Introduction
2 History of Interface Changes
3 Standalone Visualizations
4 Article-Level Inequalities
5 Article-Level Visualizations
6 Why Visualizations Haven´t Been Accepted
7 Possible Solutions
References
Part IV: Transparency in Social Media: Ethical and Critical Dimensions
Truth Telling and Deception in the Internet Society
1 Truth or Consequences
2 The Principle of Witness
3 Evasion Tactics
4 Robots Have Limitations
5 Using Computers Correctly
6 Institutions Are Essential
7 An Experimental Test
8 Some Important Metrics
9 New Institutions of Speech
References
Embedding Privacy and Ethical Values in Big Data Technology
1 Introduction
2 Defining Big Data
3 Ethical Issues in the Use of Big Data
3.1 Defining Privacy
3.2 Four Normative Principles as Basis for the Ethical Analysis of Privacy
3.3 Remarks and Explanations
3.4 Contexts of Privacy
4 The Privacy Matrix: How to Think About Privacy in Big Data
4.1 Profiling Individuals with Big Data
4.2 Anonymity, Manipulation and User Consent in Online Communities
4.3 Protecting Vulnerable Populations in Educational Contexts
4.4 Unequal Access to Big Data in Scientific Research
4.5 Big Data and Government Surveillance
4.6 Sale of Big Data in Commercial Contexts
5 Embedding Values in Big Data Technology
5.1 Values Guide the Use of Big Data Technology
5.2 Big Data Tools Enable Realization of Values
5.3 Basing Big Data Tool Design on Target Values
6 Conclusion
References
Critical Thinking and Socio-Technical Methods for Ascertaining Credibility Online
1 Introduction
2 Online Interaction, Virtual Community: The Promises of the Internet Revolution
3 Trust, Credibility, Equality? Understanding the Social Processes That Define Content Production an
Transparency in Social Media
Tools, Methods and Algorithms for Mediating Online Interactions
The volume presents, in a synergistic manner, significant theoretical and practical contributions in the area of social media reputation and authorship measurement, visualization, and modeling. The book justifies and proposes contributions to a future agenda for understanding the requirements for making social media authorship more transparent. Building on work presented in a previous volume of this series, Roles, Trust, and Reputation in Social Media Knowledge Markets, this book discusses new tools, applications, services, and algorithms that are needed for authoring content in a real-time publishing world. These insights may help people who interact and create content through social media better assess their potential for knowledge creation. They may also assist in analyzing audience attitudes, perceptions, and behavior in informal social media or in formal organizational structures. In addition, the volume includes several chapters that analyze the higher order ethical, critical thinking, and philosophical principles that may be used to ground social media authorship. Together, the perspectives presented in this volume help us understand how social media content is created and how its impact can be evaluated. The chapters demonstrate thought leadership through new ways of constructing social media experiences and making traces of social interaction visible. Transparency in Social Media aims to help researchers and practitioners design services, tools, or methods of analysis that encourage a more transparent process of interaction and communication on social media. Knowing who has added what content and with what authority to a specific online social media project can help the user community better understand, evaluate and make decisions and, ultimately, act on the basis of such information.
9783319185514
302.231 / MAT