A lecture on trust, privacy and blockchain applications given to Master's and PhD students taking a course on Social Media at the École Polytechnique Fédérale de Lausanne (EPFL). The lecture uses research conducted in the domain of digital education as a case study and has been given yearly since 2018.
Stakeholder inclusiveness as argument pro homine in CSR reportsCraig Carroll
Cite as: Carroll, CE. (2014, May) " Stakeholder inclusiveness as argument pro homine in CSR reports." International Communication Association, Seattle, WA.
5 Reputation Missteps (And how to avoid them)Bryce Glass
Web2.0 Expo presentation from F Randall Farmer and Bryce Glass, authors of the O'Reilly / Yahoo! Press book "Building Web Reputation Systems."
This talk addresses five common fallacies in designing your site or community's reputation system.
The Architecture of Social Websites: ReputationBryce Glass
The Reputation-specific slides from our IA Summit 2009 Workshop, The Architecture of Social Websites. Workshop given by Christina Wodtke, Joshua Porter, Christian Crumlish, and myself Bryce Glass.
Understanding people comes in a lot of flavors. An uncommon flavor is understanding people deeper than explanations and opinions. It's getting inside people’s minds to see how they achieve their larger human intentions and purposes without reference to your organization. The goal is to allow for later inspiration that represents the complicated inner world of people's approaches, rather than being constrained by existing systems and conventions.
After re-framing the problem as if your organization does not exist, you come back to reality with deeper understanding that influences your solutions.
Indi will define this deeper understanding, outline how collect the data, and show how to curate the knowledge in a depiction of the reasoning-patterns (mental model diagrams) and the thinking-styles (behavioral audience segments).
Stakeholder inclusiveness as argument pro homine in CSR reportsCraig Carroll
Cite as: Carroll, CE. (2014, May) " Stakeholder inclusiveness as argument pro homine in CSR reports." International Communication Association, Seattle, WA.
5 Reputation Missteps (And how to avoid them)Bryce Glass
Web2.0 Expo presentation from F Randall Farmer and Bryce Glass, authors of the O'Reilly / Yahoo! Press book "Building Web Reputation Systems."
This talk addresses five common fallacies in designing your site or community's reputation system.
The Architecture of Social Websites: ReputationBryce Glass
The Reputation-specific slides from our IA Summit 2009 Workshop, The Architecture of Social Websites. Workshop given by Christina Wodtke, Joshua Porter, Christian Crumlish, and myself Bryce Glass.
Understanding people comes in a lot of flavors. An uncommon flavor is understanding people deeper than explanations and opinions. It's getting inside people’s minds to see how they achieve their larger human intentions and purposes without reference to your organization. The goal is to allow for later inspiration that represents the complicated inner world of people's approaches, rather than being constrained by existing systems and conventions.
After re-framing the problem as if your organization does not exist, you come back to reality with deeper understanding that influences your solutions.
Indi will define this deeper understanding, outline how collect the data, and show how to curate the knowledge in a depiction of the reasoning-patterns (mental model diagrams) and the thinking-styles (behavioral audience segments).
Brain Science and Websites: 6 Ways to Leverage Cognitive Biassemrush_webinars
Call it neuromarketing. Call it behavioral economics. Call it Jedi mind tricks. Whatever you call it: brain science and marketing go together. And anyone can learn how to do it. In this presentation, we’ll review the research, case studies and web marketing tactics that work with natural, human behavioral tendencies.
Herds, halos and the science of social proof
Context, contrast and color
Fear, loss and scarcity
Eye tracking, color and visual prominence
Writing copy for busy minds
We'll reveal secrets of the brain, behavior and marketing on the web. If there are humans in your target audience, this presentation is for you.
Neuromarketing: The Brain Science of Web MarketingWebVisions
Call it neuromarketing. Call it behavioral economics. Call it Jedi mind tricks. Whatever you call it: brain science and marketing go together. And anyone can learn how to do it.
In this presentation, Andy will review the research, the case studies and the specific web marketing tactics that work with natural, human behavioral tendencies.
• Herds, Halos and How to use Social Proof
• Calls to Action? Or Calls to Conform?
• Context, contrast and the power of priming
• Fear, Loss and Scarcity
• Eye tracking, Design and Busy Minds
We'll reveal secrets of marketing masters with specific examples of the relationship between the brain, behavior and marketing on the web. If there are humans in your target audience, this presentation is for you.
Slides for talk at Forefront, Leeds, on Wednesday 26 November 2014 on considering the work of marketers in the 1930s to help us create more meaningful 'users' to create products round, by observing real people.
Researchers, Discovery and the Internet: What Next?David Smith
A web2.0 issues and implications overview I put together for the Research Information Network as part of their workshop on researchers and discovery services.
http://www.rin.ac.uk/discovery-services-workshop
Brain science and web marketing go together. And anyone can learn how to do it.
In this presentation, we’ll review the neuromarketing research, case studies and web marketing tactics that work with natural, human behavioral tendencies.
• Herds, halos and the science of social proof
• Context, contrast and color
• Fear, loss and scarcity
• Eye tracking, color and visual prominence
• Writing copy for busy minds
We'll reveal secrets of the brain, behavior and marketing on the web. If there are humans in your target audience, this presentation is for you.
The ideal attendee has 2+ years of digital marketing experience. Space is limited. Register before your competition does.
Learn the secrets of the brain, behavior and marketing. We’ll break down the marketing tactics that work with natural human tendencies. If there are humans in your target audience, this presentation is for you.
The ultimate guide to data storytelling | MaterclassGramener
Gramener collaborated with Nasscom to conduct an online masterclass session on "Storytelling With Data." Gramener's CEO, S Anand, led the masterclass and shared some important slides on how to make data stories and how to drive storytelling.
The slides talk about the structure of data stories and how to find meaning full insights from data. There are real-time examples of data analysis and visualizations we created a Gramener to communicate insights as stories.
This is an ultimate guide on data storytelling that offers tips to create data stories, things to keep in mind while making storylines, and choosing designs to make a design-led data story.
Know more about Gramener's data storytelling workshop for analysts and data scientists at https://gramener.com/data-storytelling-workshop
Product Anonymous: After Research - Creating Useful & Well Executed Research ...Jess Nichols
So you’ve completed your customer interviews - but now what?
How do you make sure that you’re creating the right insights based on all of your data? How do you advocate for your findings across product development, especially when they conflict with business objectives?
In this presentation, Jess will share how to set yourself up for success in the most important part of the user research journey - After Research. Learn how to effectively synthesise your qualitative data, create reusable and actionable insights & advocate your research across your team.
Brain Science and Websites: 6 Ways to Leverage Cognitive Biassemrush_webinars
Call it neuromarketing. Call it behavioral economics. Call it Jedi mind tricks. Whatever you call it: brain science and marketing go together. And anyone can learn how to do it. In this presentation, we’ll review the research, case studies and web marketing tactics that work with natural, human behavioral tendencies.
Herds, halos and the science of social proof
Context, contrast and color
Fear, loss and scarcity
Eye tracking, color and visual prominence
Writing copy for busy minds
We'll reveal secrets of the brain, behavior and marketing on the web. If there are humans in your target audience, this presentation is for you.
Neuromarketing: The Brain Science of Web MarketingWebVisions
Call it neuromarketing. Call it behavioral economics. Call it Jedi mind tricks. Whatever you call it: brain science and marketing go together. And anyone can learn how to do it.
In this presentation, Andy will review the research, the case studies and the specific web marketing tactics that work with natural, human behavioral tendencies.
• Herds, Halos and How to use Social Proof
• Calls to Action? Or Calls to Conform?
• Context, contrast and the power of priming
• Fear, Loss and Scarcity
• Eye tracking, Design and Busy Minds
We'll reveal secrets of marketing masters with specific examples of the relationship between the brain, behavior and marketing on the web. If there are humans in your target audience, this presentation is for you.
Slides for talk at Forefront, Leeds, on Wednesday 26 November 2014 on considering the work of marketers in the 1930s to help us create more meaningful 'users' to create products round, by observing real people.
Researchers, Discovery and the Internet: What Next?David Smith
A web2.0 issues and implications overview I put together for the Research Information Network as part of their workshop on researchers and discovery services.
http://www.rin.ac.uk/discovery-services-workshop
Brain science and web marketing go together. And anyone can learn how to do it.
In this presentation, we’ll review the neuromarketing research, case studies and web marketing tactics that work with natural, human behavioral tendencies.
• Herds, halos and the science of social proof
• Context, contrast and color
• Fear, loss and scarcity
• Eye tracking, color and visual prominence
• Writing copy for busy minds
We'll reveal secrets of the brain, behavior and marketing on the web. If there are humans in your target audience, this presentation is for you.
The ideal attendee has 2+ years of digital marketing experience. Space is limited. Register before your competition does.
Learn the secrets of the brain, behavior and marketing. We’ll break down the marketing tactics that work with natural human tendencies. If there are humans in your target audience, this presentation is for you.
The ultimate guide to data storytelling | MaterclassGramener
Gramener collaborated with Nasscom to conduct an online masterclass session on "Storytelling With Data." Gramener's CEO, S Anand, led the masterclass and shared some important slides on how to make data stories and how to drive storytelling.
The slides talk about the structure of data stories and how to find meaning full insights from data. There are real-time examples of data analysis and visualizations we created a Gramener to communicate insights as stories.
This is an ultimate guide on data storytelling that offers tips to create data stories, things to keep in mind while making storylines, and choosing designs to make a design-led data story.
Know more about Gramener's data storytelling workshop for analysts and data scientists at https://gramener.com/data-storytelling-workshop
Product Anonymous: After Research - Creating Useful & Well Executed Research ...Jess Nichols
So you’ve completed your customer interviews - but now what?
How do you make sure that you’re creating the right insights based on all of your data? How do you advocate for your findings across product development, especially when they conflict with business objectives?
In this presentation, Jess will share how to set yourself up for success in the most important part of the user research journey - After Research. Learn how to effectively synthesise your qualitative data, create reusable and actionable insights & advocate your research across your team.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Online aptitude test management system project report.pdfKamal Acharya
The purpose of on-line aptitude test system is to take online test in an efficient manner and no time wasting for checking the paper. The main objective of on-line aptitude test system is to efficiently evaluate the candidate thoroughly through a fully automated system that not only saves lot of time but also gives fast results. For students they give papers according to their convenience and time and there is no need of using extra thing like paper, pen etc. This can be used in educational institutions as well as in corporate world. Can be used anywhere any time as it is a web based application (user Location doesn’t matter). No restriction that examiner has to be present when the candidate takes the test.
Every time when lecturers/professors need to conduct examinations they have to sit down think about the questions and then create a whole new set of questions for each and every exam. In some cases the professor may want to give an open book online exam that is the student can take the exam any time anywhere, but the student might have to answer the questions in a limited time period. The professor may want to change the sequence of questions for every student. The problem that a student has is whenever a date for the exam is declared the student has to take it and there is no way he can take it at some other time. This project will create an interface for the examiner to create and store questions in a repository. It will also create an interface for the student to take examinations at his convenience and the questions and/or exams may be timed. Thereby creating an application which can be used by examiners and examinee’s simultaneously.
Examination System is very useful for Teachers/Professors. As in the teaching profession, you are responsible for writing question papers. In the conventional method, you write the question paper on paper, keep question papers separate from answers and all this information you have to keep in a locker to avoid unauthorized access. Using the Examination System you can create a question paper and everything will be written to a single exam file in encrypted format. You can set the General and Administrator password to avoid unauthorized access to your question paper. Every time you start the examination, the program shuffles all the questions and selects them randomly from the database, which reduces the chances of memorizing the questions.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
9. “Trust… is a particular level of the subjective probability with
which an agent assesses that another agent or group of
agents will perform a particular action, both before he can
monitor such action… and in a context in which it affects his
own action.”
Diego Gambetta, Can We Trust Trust? (2000)
10. “Trust… is a particular level of the subjective probability with
which an agent assesses that another agent or group of
agents will perform a particular action, both before he can
monitor such action… and in a context in which it affects his
own action.”
Diego Gambetta, Can We Trust Trust? (2000)
11. “Trust… is a particular level of the subjective probability with
which an agent assesses that another agent or group of
agents will perform a particular action, both before he can
monitor such action… and in a context in which it affects his
own action.”
Diego Gambetta, Can We Trust Trust? (2000)
12. “Trust… is a particular level of the subjective probability with
which an agent assesses that another agent or group of
agents will perform a particular action, both before he can
monitor such action… and in a context in which it affects his
own action.”
Diego Gambetta, Can We Trust Trust? (2000)
13. “Trust… is a particular level of the subjective probability with
which an agent assesses that another agent or group of
agents will perform a particular action, both before he can
monitor such action… and in a context in which it affects his
own action.”
Diego Gambetta, Can We Trust Trust? (2000)
14. “Trust… is a particular level of the subjective probability with
which an agent assesses that another agent or group of
agents will perform a particular action, both before he can
monitor such action… and in a context in which it affects his
own action.”
Diego Gambetta, Can We Trust Trust? (2000)
15. “Trust is in the end a practical matter. It’s a question of trying
to place it intelligently. [...] With trust, you want to trust things
that are trustworthy and mistrust what’s untrustworthy. And in
both cases the evidence is incomplete and it’s quite difficult.”
Onora O’Neill, Trust, BBC Radio 4 Analysis (2011)
16. “Trust is in the end a practical matter. It’s a question of trying
to place it intelligently. [...] With trust, you want to trust things
that are trustworthy and mistrust what’s untrustworthy. And in
both cases the evidence is incomplete and it’s quite difficult.”
Onora O’Neill, Trust, BBC Radio 4 Analysis (2011)
18. Motivation: Measuring Trust / Trustworthiness
- What are some ways in which this could be achieved?
- Surveys
- General Social Survey (GSS)
- World Values Survey
- Often questions or statements like:
- “Most people can be trusted.”
- “You can’t be too careful in dealing with people.”
19. Motivation: Measuring Trust / Trustworthiness
- What are some ways in which this could be achieved?
- Surveys
- General Social Survey (GSS)
- World Values Survey
- Often questions or statements like:
- “Most people can be trusted.”
- “You can’t be too careful in dealing with people.”
- Experiments
- The Trust Game (Berg et al., Trust, Reciprocity and Social History, 1995).
- One subject is given 15 USD to give to a second subject. Amount given is
tripled/doubled. Receiver can then give back some amount to first subject.
- Endless variations.
20. Motivation: Measuring Trust / Trustworthiness
- What are some ways in which this could be achieved?
- Surveys
- General Social Survey (GSS)
- World Values Survey
- Often questions or statements like:
- “Most people can be trusted.”
- “You can’t be too careful in dealing with people.”
- Experiments
- The Trust Game (Berg et al., Trust, Reciprocity and Social History, 1995).
- One subject is given 15 USD to give to a second subject. Amount given is
tripled/doubled. Receiver can then give back some amount to first subject.
- Endless variations.
- Proxies
- Role within a Social Network
- Reputation
21. Motivation: Reputation
- “Reputation is information used to make a value judgment about an object
or a person.”
- Value judgments can be decisive, continuous and expressive.
- E.g. thumbs up, favourite, rating, review, etc.
- The object or person in question is a reputable entity (i.e. can have a reputation).
- The information is a reputation statement.
- E.g. a city is worth visiting, an article is worth reading, a movie is bad.
F. Randall Farmer, Bryce Glass, Building Web Reputation
Systems, 2010.
22. Motivation: Reputation
- “Reputation is information used to make a value judgment about an object
or a person.”
- Value judgments can be decisive, continuous and expressive.
- E.g. thumbs up, favourite, rating, review, etc.
- The object or person in question is a reputable entity (i.e. can have a reputation).
- The information is a reputation statement.
- E.g. a city is worth visiting, an article is worth reading, a movie is bad.
- Reputation takes place within a context (geography, subject, purpose).
- E.g. local universities, winter tires, abstract art, etc.
F. Randall Farmer, Bryce Glass, Building Web Reputation
Systems, 2010.
23. Motivation: Reputation
- “Reputation is information used to make a value judgment about an object
or a person.”
- Value judgments can be decisive, continuous and expressive.
- E.g. thumbs up, favourite, rating, review, etc.
- The object or person in question is a reputable entity (i.e. can have a reputation).
- The information is a reputation statement.
- E.g. a city is worth visiting, an article is worth reading, a movie is bad.
- Reputation takes place within a context (geography, subject, purpose).
- E.g. local universities, winter tires, abstract art, etc.
- Reputation is often limited in scope, which can or not be surfaced globally.
- E.g. favourite restaurants vs internal employee reviews.
F. Randall Farmer, Bryce Glass, Building Web Reputation
Systems, 2010.
24. Motivation: Reputation
- “Reputation is information used to make a value judgment about an object
or a person.”
- Value judgments can be decisive, continuous and expressive.
- E.g. thumbs up, favourite, rating, review, etc.
- The object or person in question is a reputable entity (i.e. can have a reputation).
- The information is a reputation statement.
- E.g. a city is worth visiting, an article is worth reading, a movie is bad.
- Reputation takes place within a context (geography, subject, purpose).
- E.g. local universities, winter tires, abstract art, etc.
- Reputation is often limited in scope, which can or not be surfaced globally.
- E.g. favourite restaurants vs internal employee reviews.
- “[Reputation] brings structure to chaos by allowing us to proxy trust when
making day-to-day decisions.” F. Randall Farmer, Bryce Glass, Building Web Reputation
Systems, 2010.
25. Motivation: Reputation Models
- What are some common (web-based) reputation models?
F. Randall Farmer, Bryce Glass, Building Web Reputation
Systems, 2010.
26. - Favourites and Flags (Reddit)
- Vote to Promote
- Favourites
- Report Abuse
Motivation: Reputation Models
F. Randall Farmer, Bryce Glass, Building Web Reputation
Systems, 2010.
27. Motivation: Reputation Models
- Favourites and Flags (Reddit)
- Vote to Promote
- Favourites
- Report Abuse
- This-or-That Voting (Amazon)
F. Randall Farmer, Bryce Glass, Building Web Reputation
Systems, 2010.
28. Motivation: Reputation Models
- Favourites and Flags
- Vote to Promote
- Favourites
- Report Abuse
- This-or-That Voting (Amazon)
- Ratings (Uber)
F. Randall Farmer, Bryce Glass, Building Web Reputation
Systems, 2010.
29. Motivation: Reputation Models
- Favourites and Flags (Reddit)
- Vote to Promote
- Favourites
- Report Abuse
- This-or-That Voting (Amazon)
- Ratings (Uber)
- Reviews (Airbnb)
F. Randall Farmer, Bryce Glass, Building Web Reputation
Systems, 2010.
30. Motivation: Reputation Models
- Favourites and Flags (Reddit)
- Vote to Promote
- Favourites
- Report Abuse
- This-or-That Voting (Amazon)
- Ratings (Uber)
- Reviews (Airbnb)
- Points (Stack Overflow)
F. Randall Farmer, Bryce Glass, Building Web Reputation
Systems, 2010.
32. Motivation: Defining Trust and Trustworthiness
- The definition of trust changes in accordance to the domain and context.
- Throughout this lecture, we should keep in mind how the ideas of trust and
reputation apply to the concepts at hand.
- Some questions to keep in mind:
- Do we trust the services that we use? Why?
- Do we trust their infrastructure? Why?
- Do we trust the people behind them? Why?
33. Motivation: Why is trust important?
“[Trust] matters because the world is quite uncertain and
getting it right is very useful. It’s very useful if I know whom I
can rely on for which purpose and whom I can’t rely on.”
Onora O’Neill, Trust, BBC Radio 4 Analysis (2011)
34. Motivation: Why is trust important?
More lightly speaking... how would your behaviour change
if you were not sure you could trust [ ]?
36. “No one must be subjected to arbitrary interference with his
privacy, family, home or correspondence, nor to attacks upon
his honor and reputation.”
Article 12, Universal Declaration of Human Rights
37. Motivation: Privacy
- The Universal Declaration of Human Rights tells us that we need to value our
own, and respect others’ privacy.
- But what exactly is privacy?
38. Motivation: What is privacy?
1. Privacy is a relational concept. It comes to the fore in a community. Where
people interact, the issue of privacy emerges.
Lucas D. Introna, Privacy and the computer: why we need
privacy in the information society, Metaphilosophy, 1997.
39. Motivation: What is privacy?
1. Privacy is a relational concept. It comes to the fore in a community. Where
people interact, the issue of privacy emerges.
2. Privacy is directed towards the personal domain. What is deemed
personal is, to some extent at least, culturally defined.
Lucas D. Introna, Privacy and the computer: why we need
privacy in the information society, Metaphilosophy, 1997.
40. Motivation: What is privacy?
1. Privacy is a relational concept. It comes to the fore in a community. Where
people interact, the issue of privacy emerges.
2. Privacy is directed towards the personal domain. What is deemed
personal is, to some extent at least, culturally defined.
3. To claim privacy is to claim the right to limit access or control access to my
personal or private domain.
Lucas D. Introna, Privacy and the computer: why we need
privacy in the information society, Metaphilosophy, 1997.
41. Motivation: What is privacy?
1. Privacy is a relational concept. It comes to the fore in a community. Where
people interact, the issue of privacy emerges.
2. Privacy is directed towards the personal domain. What is deemed
personal is, to some extent at least, culturally defined.
3. To claim privacy is to claim the right to limit access or control access to my
personal or private domain.
4. An effective way to control access to my personal realm is to control the
distribution of textual images or verbal information about it.
Lucas D. Introna, Privacy and the computer: why we need
privacy in the information society, Metaphilosophy, 1997.
42. Motivation: What is privacy?
1. Privacy is a relational concept. It comes to the fore in a community. Where
people interact, the issue of privacy emerges.
2. Privacy is directed towards the personal domain. What is deemed
personal is, to some extent at least, culturally defined.
3. To claim privacy is to claim the right to limit access or control access to my
personal or private domain.
4. An effective way to control access to my personal realm is to control the
distribution of textual images or verbal information about it.
5. To claim privacy is to claim the right to a (personal) domain of immunity
against the judgments of others.
Lucas D. Introna, Privacy and the computer: why we need
privacy in the information society, Metaphilosophy, 1997.
43. Motivation: What is privacy?
1. Privacy is a relational concept. It comes to the fore in a community. Where
people interact, the issue of privacy emerges.
2. Privacy is directed towards the personal domain. What is deemed
personal is, to some extent at least, culturally defined.
3. To claim privacy is to claim the right to limit access or control access to my
personal or private domain.
4. An effective way to control access to my personal realm is to control the
distribution of textual images or verbal information about it.
5. To claim privacy is to claim the right to a (personal) domain of immunity
against the judgments of others.
6. Privacy is a relative concept. It is a continuum. Total privacy may be as
undesirable as total transparency. Lucas D. Introna, Privacy and the computer: why we need
privacy in the information society, Metaphilosophy, 1997.
44. Motivation: Why is privacy important?
“Privacy is necessary to the creation of selves out of human beings, since a self is
at least in part a human being who regards his existence, his thoughts, his body,
his actions as his own.”
- Jeffrey H. Reinman, Privacy, Intimacy, and Personhood, 1976
45. Motivation: Why is privacy important?
“Privacy is necessary to the creation of selves out of human beings, since a self is
at least in part a human being who regards his existence, his thoughts, his body,
his actions as his own.”
- Jeffrey H. Reinman, Privacy, Intimacy, and Personhood, 1976
“Privacy contributes to the formation and persistence of autonomous individuals by
providing them with control over whether or not their physical and psychological
existence becomes part of another’s experience. Just this sort of control is
necessary for them to think of themselves as self-determining.”
- Joseph Kupfer, Privacy, Autonomy, and Self-Concept, 1987
46. Motivation: Why is privacy important?
More lightly speaking... would you act the same if you
knew that someone was observing you?
47. Motivation: Privacy is Important
- In 1890, Samuel Warren and Louis Brandeis publish “The
Right to Privacy”, in the Harvard Law Review.
- Considered an touchstone of modern privacy law.
- They were quite concerned about new technologies and the
role of the press in society.
- “If we are correct… the existing law affords a principle which
may be invoked to protect the privacy of the individual from
invasion either by the too enterprising press, the
photographer, or the possessor of any other modern device
for recording or reproducing scenes or sounds.” Louis Brandeis
Source: Wikipedia
Samuel D. Warren and Louis D. Brandeis, The Right to Privacy,
Harvard Law Review, Vol. 4, No. 5. (Dec. 15, 1890), pp. 193-220.
48. Motivation: But is privacy really that important?
Jeremy Bentham (1748 - 1832)
Source: Wikipedia
49. Motivation: But is privacy really that important?
- Panopticism: From the Greek παν- “all” and -οπτικος “seeing”
- In the late 18th century, English philosopher Jeremy Bentham proposed the
panopticon in the context of prisons.
- Concept:
- Constant surveillance.
- Inmates cannot know when the watchman is observing them.
- Inmates regulate their own behaviour.
“Morals reformed—health preserved—industry invigorated—
instruction diffused—public burthens lightened…”
50. A panopticon building at Presidio Modelo prison in Cuba.
Photo Credit: Tod Seelie.
Atlas Obscura, 19 June 2017
51. Motivation: But is privacy really that important?
- In 1975, French philosopher Michel Foucault revisited the panopticon in his
book Discipline and Punish.
- There are panoptic methods operated throughout a disciplinary society (in
schools, factories, hospitals, military regiments, prison), which allows it to
keep its citizens under control and conforming to certain norms.
- Discipline, through these methods, creates “docile bodies”.
- Docile bodies are “something that can be made; out of a formless clay,
an inapt body [from which] the machine required can be constructed.”
- Importance of training.
52. Motivation: But is privacy really that important?
- Put in the context of privacy, Introna explains that “the transparency—the
universal ‘gaze’—created by the panopticon effect (universal and continual
surveillance) leads to the internalization of man. In his self-surveillance, man
cultivates a self-consciousness. Thus, Foucault argues that our world is de
facto transparent and that privacy is impossible, since ultimately we always
observe ourselves.”
56. Motivation: Cambridge Analytica
- British data analytics firm.
- Harvested personal data from over 50 million Facebook profiles without
permission.
- Built a system that targeted voters in the US with political ads based on their
personal profile.
- Employees were “filmed boasting of using manufactured sex scandals, fake
news and dirty tricks to swing elections around the world”.
The Guardian, 26 March 2018
60. Motivation: GDPR
- GDPR stands for General Data Protection Regulation.
- It came into effect on 25 May 2018.
- “GDPR is a vast piece of legislation which grants people living in Europe new
powers over the data being collected about them—like the right to access or
delete their own data, and the need for their consent to use it.”
- “The maximum fine for non-compliance with GDPR is 4% of annual turnover
or €20 million ($24.6 million).”
Forbes, 2 May 2018
66. “You could say that blockchain is the ultimate ‘anti-trust’
technology. That’s not only because it facilitates transactions
between parties that don’t have to trust each other, but also
because it doesn’t rely on a single source of power with total
control of a market, like old-fashioned ‘trusts’.”
Derek Thompson, It Is Silly Season in the Land of
Cryptocurrency, The Atlantic, 10 January 2018.
67. This is how blockchain was doing three years ago.
Blockchain
Gartner, 15 August 2017
68. And this is how it was doing in 2018.
Blockchain
Gartner, 16 August 2018
69. This year, it is deep in the trough of disillusionment. But
many specific blockchain uses are on the rise.
Gartner, 12 September 2019
Blockchain
71. Motivation: ICOs
- ICO stands for Initial Coin Offering.
- It is a fundraising strategy, commonly used by blockchain startups.
- It consists of selling crypto tokens in exchange for a cryptocurrency.
72. Motivation: ICOs
- ICO stands for Initial Coin Offering.
- It is a fundraising strategy, commonly used by blockchain startups.
- It consists of selling crypto tokens in exchange for a cryptocurrency.
- Each project usually has its own token(s).
- Equity Tokens: Share in the project or company.
- Utility Tokens: Can be used in the application that is being created.
- Asset Tokens: Represent a physical asset or product (e.g. gold).
- Reputation Tokens: Represents a user’s reputation.
73. Motivation: ICOs
- ICO stands for Initial Coin Offering.
- It is a fundraising strategy, commonly used by blockchain startups.
- It consists of selling crypto tokens in exchange for a cryptocurrency.
- Each project usually has its own token(s).
- Equity Tokens: Share in the project or company.
- Utility Tokens: Can be used in the application that is being created.
- Asset Tokens: Represent a physical asset or product (e.g. gold).
- Reputation Tokens: Represents a user’s reputation.
- According to The State of the Token Market 2017 report, more than 5.6 billion
USD of capital was raised in 2017 through ICOs. At the end of Q3 2018, this
number was 12.3 billion USD (The State of the Token Market 2018).
- However, we’re still waiting for the 2019 report.
74. Takeaway 3:
There is a lot of hype, but also
a lot of money being invested
in the blockchain space.
76. “The technology at the heart of bitcoin and other virtual
currencies, blockchain is an open, distributed ledger that
can record transactions between two parties efficiently and in
a verifiable and permanent way.”
Marco Iansiti and Karim R. Lakhani. The Truth about
Blockchain, Harvard Business Review 95, no. 1
(January–February 2017): 118–127.
77. Blockchain: What is a blockchain?
- Originally the distributed ledger on which Bitcoin transactions are recorded.
- It employs cryptographic functions to create an append-only,
tamper-evident log.
- Verifiable
- Permanent
- Items get inscribed only if approved by the majority of participants (peers) in
the network.
- Consensus
80. Blockchain: Cryptographic Hash Functions
- Mathematical algorithm that takes as input a message of arbitrary length and
outputs a message digest of fixed length.
81. Blockchain: Cryptographic Hash Functions
- Mathematical algorithm that takes as input a message of arbitrary length and
outputs a message digest of fixed length.
- Key properties:
- Deterministic: Same message always generates the same digest.
- Efficient: Fast computation of digest from message.
- Collision-Free: Infeasible to find two different messages with the same digest.
- Hiding: Digest does not reveal information about the message.
- One-Way: Infeasible to generate a message from its digest.
82. Blockchain: Cryptographic Hash Functions
- Mathematical algorithm that takes as input a message of arbitrary length and
outputs a message digest of fixed length.
- Key properties:
- Deterministic: Same message always generates the same digest.
- Efficient: Fast computation of digest from message.
- Collision-Free: Infeasible to find two different messages with the same digest.
- Hiding: Digest does not reveal information about the message.
- One-Way: Infeasible to generate a message from its digest.
- Examples:
- MD5: Insecure. Used for checking data integrity (checksum). (Try it out: bit.ly/2jFEJvN)
- SHA-256: Secure. Used by the Bitcoin blockchain. (Try it out: bit.ly/2IobpaZ)
83. Blockchain: SHA-256
- Example 1:
- Input: The quick brown fox jumps over the lazy dog. (Message)
- Output: EF537F25C895BFA782526529A9B63D97AA631564D5D789C2B765448C8635FB6C (SHA-256 Digest)
84. Blockchain: SHA-256
- Example 1:
- Input: The quick brown fox jumps over the lazy dog. (Message)
- Output: EF537F25C895BFA782526529A9B63D97AA631564D5D789C2B765448C8635FB6C (SHA-256 Digest)
- Example 2:
- Input 2: The quick brown fox jumps over the lazy dog (Message)
- Output 2: D7A8FBB307D7809469CA9ABCB0082E4F8D5651E46D3CDB762D02D0BF37C9E592 (SHA-256 Digest)
88. Blockchain: Append-Only, Tamper-Evident
- Blocks Appended. New transactions are registered on the blockchain by
appending a block to the chain.
- Hash Pointers. For a block to be appended, it has to include the
cryptographic hash of the previous block. This ensures that by having the
hash at the end of the chain, you can confirm the integrity of all previous
blocks.
- Temporary Forks. It is possible that two blocks can be generated at the
same time and appended to the blockchain. These “forks” are temporary.
- Longest Chain. The “longest” chain is considered to be the valid one.
Well-behaved peers are expected to follow this.
89. Blocks are appended and include a hash pointer to the
previous block on the chain. This makes the blockchain
structure tamper-evident.
10 11 12
90. Let’s say we know the hash at the head of the list.
10 11 12
91. Now let’s say a malicious agent wants to tamper with data in block 10.
10 11 12
92. The agent will also have to modify the hash pointer in block 11.
10 11 12
93. As well as the hash pointer in block 12.
10 11 12
94. At this point, we know someone has tampered with the data
because we remember the hash at the head of the list.
!
10 11 12
95. It is possible that two blocks can be generated at the
same time and appended to the blockchain temporarily.
97. Now let’s say two nodes add a block to the chain at the
same time.
Green Lead: 1 Red Lead: 1
98. They will propagate this chain through the network.
Red Lead: 4Green Lead: 10
99. The chain with the leading green block spreads faster
because of the topology of the network.
Red Lead: 9Green Lead: 22
100. Now let’s say one of the green nodes appends a yellow
block to the chain. This is now the longest chain.
Yellow Lead: 1
Red Lead: 9Green Lead: 21
101. At this point, the last nodes could receive any of the three
versions of the blockchain. It all depends on timing.
Yellow Lead: 5
Red Lead: 12Green Lead: 27
102. But let’s say that they receive the chain with the leading
red block.
Yellow Lead: 5
Red Lead: 15Green Lead: 27
103. When they then receive the chain with the leading yellow
block, they will see that it’s longer and ignore the red block.
Yellow Lead: 15
Red Lead: 11Green Lead: 21
104. Eventually, the whole network will have the chain with the
leading yellow block.
Yellow Lead: 47
Red Lead: 0Green Lead: 0
105. The red block will be left on a “temporary” fork of the
chain. These blocks are referred to as “orphaned”.
107. Blockchain: Uses
- Blockchain has been proposed as the core building block of decentralized
applications in various sectors where user privacy and data authenticity is
paramount, including finance, telecommunications, and healthcare.
108. Blockchain: Evolution
Blockchain 1.0: The Bitcoin Blockchain
(Internet Analogy: “Transport Layer TCP/IP”)
- Currency
- Escrow, Contracts, Arbitration, Multiparty Signatures
Melanie Swan, Blockchain for a New Economy, 2015.
109. Blockchain: Evolution
Blockchain 1.0: The Bitcoin Blockchain
(Internet Analogy: “Transport Layer TCP/IP”)
- Currency
- Escrow, Contracts, Arbitration, Multiparty Signatures
Blockchain 2.0: Smart Contracts
(Internet Analogy: “Protocols HTTP/SMTP/FTP”)
- Other assets beyond currency. Recall the tokens.
- Ethereum introduces a Turing-complete virtual machine.
- Distributed Applications (DApps)
- Distributed Autonomous Organisations (DAOs)
Melanie Swan, Blockchain for a New Economy, 2015.
110. Blockchain: Evolution
Blockchain 3.0: Applications Beyond Currency Economics and Markets
(Internet Analogy: “HTML, Email”)
- Blockchain Science
- Blockchain Genomics
- Blockchain Health
- Blockchain Learning
- ...
Melanie Swan, Blockchain for a New Economy, 2015.
113. Blockchain: Challenges
- “To make effective progress in this area you need to bring together a
combination of a large number of interdisciplinary skills and perspectives…
You don’t just need excellent technical people… but you can’t also forget
about for example your experts in business processes, economics, security
and privacy and the law.”
- “How can ordinary people have faith that the contracts they are signing up to
are what they really think they’re signing up to without becoming experts in
reading smart contract code.”
- “We need mechanisms to link physical objects and identities in the real world
to the virtual object on the blockchain. That’s absolutely not a simple problem,
but it’s a key step in reinforcing the trust that we have in such blockchains.”
William Knottenbelt & Catherine Mulligan, Blockchain, World Economic Forum, 21 June 2017.
114. Takeaway 5:
Blockchain could be the
underlying technology to solve
a wide array of problems in
various domains, but there are
some challenges.
118. Case Study: Graasp
- Online platform for learning spaces.
- Teachers can create learning spaces in which they can embed various types
of resources (videos, images, etc.), as well as interactive applications.
- Students then perform a learning activity inside these spaces and in doing so,
might generate activity traces (similar to Google Analytics).
120. Case Study: Premise
- Users perform a learning activity on Graasp and generate traces.
- These traces are used for educational research.
- Users can be anonymous.
121. Case Study: The Problem
- We don’t want to necessarily store activity traces ourselves, we want to allow
users to store activity traces in their own repositories. (GDPR)
- We also want to allow education researchers to run analyses on the data
users generated on our platform.
- Users can voluntarily provide their data for these studies. (GDPR)
122. Case Study: The Problem
- We don’t want to necessarily store activity traces ourselves, we want to allow
users to store activity traces in their own repositories. (GDPR)
- We also want to allow education researchers to run analyses on the data
users generated on our platform.
- Users can voluntarily provide their data for these studies. (GDPR)
- Problem: If we allow users to store their own data, how can we guarantee
that the data has not been tampered with when we retrieve it for analysis?
123. Case Study: The Problem
- We don’t want to necessarily store activity traces ourselves, we want to allow
users to store activity traces in their own repositories. (GDPR)
- We also want to allow education researchers to run analyses on the data
users generated on our platform.
- Users can voluntarily provide their data for these studies. (GDPR)
- Problem: If we allow users to store their own data, how can we guarantee
that the data has not been tampered with when we retrieve it for analysis?
- Solution: Store a hash of activity traces ourselves before sending them out.
126. Case Study: Another Problem
- Why might we not trust ourselves?
- Being an application provider does not mean that you can trust us with
your data.
- Malicious.
- Service might go offline (temporarily or permanently).
- A trustworthy company does not necessarily have trustworthy employees.
- E.g. Uber (Reveal News, 12 December 2016).
127. Case Study: Another Problem
- Why might we not trust ourselves?
- Being an application provider does not mean that you can trust us with
your data.
- Malicious.
- Service might go offline (temporarily or permanently).
- A trustworthy company does not necessarily have trustworthy employees.
- E.g. Uber (Reveal News, 12 December 2016).
- Can we trust another third-party? Can we trust the government?
- Probably, but then we might run into the same issues mentioned above.
128. Case Study: Another Problem
- Why might we not trust ourselves?
- Being an application provider does not mean that you can trust us with
your data.
- Malicious.
- Service might go offline (temporarily or permanently).
- A trustworthy company does not necessarily have trustworthy employees.
- E.g. Uber (Reveal News, 12 December 2016).
- Can we trust another third-party? Can we trust the government?
- Probably, but then we might run into the same issues mentioned above.
- Solution: Store the hash on a blockchain.
130. Recording Process: A learner’s interaction with a LE generates learning traces, which
are then put together and emitted as a learning block at the end of the learning activity.
This block is then signed and sent to an external LBR, with its hash being recorded on
the blockchain for future validation.
Farah et al., A Blueprint for a Blockchain-Based Architecture, ICALT, Mumbai, 2018.
131. Validating Process: To retrieve a learning block, the requesting party requires access
granted by the owner of the repository. If a request is legitimate and the repository is
online, a block is verified by comparing its hash to the one recorded on the blockchain
and returned if valid.
Farah et al., A Blueprint for a Blockchain-Based Architecture, ICALT, Mumbai, 2018.
132. Modular: These processes can be a part of a larger infrastructure.
Machado et al., Towards Open Data in Digital Education Platforms, 2019.
133. Modular: These processes can be a part of a larger infrastructure.
Machado et al., Towards Open Data in Digital Education Platforms, 2019.
134. Case Study: The Real Problem
- Remember Takeaway #4?
- Blockchains are complicated.
135. Case Study: The Real Problem
- Remember Takeaway #4?
- Blockchains are complicated.
- Challenges Identified
- What do you store in the blockchain?
- Privacy Issues (GDPR)
136. Case Study: The Real Problem
- Remember Takeaway #4?
- Blockchains are complicated.
- Challenges Identified
- What do you store in the blockchain?
- Privacy Issues (GDPR)
- How frequent do you write to / read from the blockchain?
- Fees
- Latency
137. Case Study: The Real Problem
- Remember Takeaway #4?
- Blockchains are complicated.
- Challenges Identified
- What do you store in the blockchain?
- Privacy Issues (GDPR)
- How frequent do you write to / read from the blockchain?
- Fees
- Latency
- Are your contracts really smart?
- Ethereum smart contracts are open source and could be exploited if vulnerable.
138. Case Study: The Real Problem
- Remember Takeaway #4?
- Blockchains are complicated.
- Challenges Identified
- What do you store in the blockchain?
- Privacy Issues (GDPR)
- How frequent do you write to / read from the blockchain?
- Fees
- Latency
- Are your contracts really smart?
- Ethereum smart contracts are open source and could be exploited if vulnerable.
- Do end users really care about the problem identified?
- We do not want to complicate user experience for no added value.
150. Conclusions: What we looked at today?
- Motivation
- Trust
- Definitions.
- Privacy
- Definitions, Breaches, Regulation
- Blockchain
- Hype
- Blockchain
- Basic Features and Applications
- Case Study
- Applying Blockchain in Educational Technology and Research.
151. Conclusions: Key Takeaway Points
1. Privacy-wise, it’s somewhat of a wild west out there on the Internet.
2. Whatever your opinion on Internet privacy, you need to treat user (especially
European user) data with care.
3. There is a lot of hype, but also a lot of money being invested in the blockchain
space.
4. Blockchain architectures are complicated, but have some pretty cool features.
5. Blockchain could be the underlying technology to solve a wide array of
problems in various domains, but there are some challenges.
6. Think well and consider your options before you use a blockchain.