Web Science
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| Home | Part1: Foundations of the web | Part2: Emerging Web properties | Part3: Behavioral Models | Part4: Web & society | Participate | About the Web Science MOOC |
Course elements
- PART1: Week1: Ethernet · Internet Protocol · Week2: Transmission Control Protocol · Domain Name System · Week3: Internet vs world wide web · HTTP · Week4: Web Content ·Dynamic Web Content
- PART2: Week5: How big is the Web? · Descriptive Web Models · Week7: Advanced Statistic Models · Modelling Similarity · Week8: Generative Modelling of the Web · Graph theoretic Web Modelling
- PART3: Week8 : Investigating Meme Spreading · Herding Behaviour · Week9: Online Advertising · User Modelling
- PART4: Week8 : Copyright · Net neutrality · Week9: Internet governance · Privacy
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Introduction (0th week)
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Web Science/Part1: Foundations of the web
Lessons
- understand the basic problems when communicating over a shared medium
- understand the origins of ethernet
- be able to name the ethernet header fields
- be able to explain the reason for the preamble
- understand that the cable length has an influence to transfer rate
- understand that speed of light is responsible for the connection between cable length and transfer rate
- be able to calculate the maximum cable length for a given transfer rate
- understand that the cable length is part of the Ethernet protocol
- Understand that Ethernet is a non deterministic program
- Be able to reconstruct a collision detection / resolve algorithm
- Understand what happens if two computers send data at the same time
- get introduced to the concept of an IP-network
- understand that networks can be interconnected
- learn about the importance for decentralization as a design principle
- realize that Local area networks can be fragmented via IP networks
- understand that an IP network as an overlay network is an abstract thing that is not directly reflecting the hardware settings
- understand the notion of an IPv4 address and its components like network and host part
- understand why MAC addresses do not fulfill the requirements of IP addresses.
- get introduced to the notion of an IP router / gateway
- review the definition and concept of an IP network
- understand that IP routing works on the level of IP networks
- understand the concept of subnetting
- review network classes and understand classless inter domain routing.
- get a feeling for the IP header
- get a better understanding of how the protocol works
- understand which header fields are changed while routing
- understand which problems of IP will be solved with the transmition control protocol
- be aware of the limitations of the internet protocol and the internet architecture
- get to know the end to end principle and in which only sender and receiver take care that communication works properly
- understand the concept of a logical connection (virtual communication channel) between two computers on the internet
- understand the importance of acknowledging received messages
- be able to understand the process of establishing a tcp / connection
- understand the concept of a socket in a TCP/IP package
- understand that ports are part of the TCP header
- be able to explain the difference between solicited and unsolicited TCP/IP traffic
- understand how ports can be used for multiplexing internet connections
- understand the concept of windowsize and sliding window
- understand how flow control can prevent TCP connections to overload link layer protocols and slow networks
- In this lesson you will learn some basics on the Question: Why Web Content needs structure and proper markup.
- Understand the Domain Object Model and the DOM tree
- Understand that HTML is just a special dialect of XML
- Understand the relationship between HTML and XML
- Be able to write simple HTML code having learned a few example elements of HTML (headings, paragraphs, lists, tables, links, anchors, emphasize, input fields; but also few dirty ones like italics, color,...)
- See that HTML really is just another simple mark up and has nothing to do with programming
- Be able to structure web Content using HTML and create pages following a specified structure.
- Know about the style attribute and how to use it within HTML elements
- Know already realize that there are some limits using the style attribute
- be able to create websites that follow a certain style guide
- See the problems with inline styles
- Understand that a style sheet gives you freedom
- being able to explain people why they should use style sheets
- be able to name at least 2 important point why to use style sheets
- know how the cascading process works
- know the basic syntax of cascading stylesheets
- know how to include a media file like a graphic to your webpage.
- understand that images like jpg, gif and bitmaps are hard for machines to understand.
- Know how to use a XML based format to create images that are easy to understand for machines and humans an can even make use of stylesheets.
- Understand that metadata is necessary to communicate the semantics of content
- See that using metadata for ranking in search results is a bad idea
- get introduced to modern ways of publishing media data as RDFa
- Understand the separation between content, structure, layout and meta data
- Review HTML, CSS, XML, SVG and RDFa
- Understand what makes a clean HTML markup ("separation of concerns") vs. unclean one ("mixing responsibilities"); and implications (better or worse maintenance, better or worse personalization, better or worse accessibility)
- become aware of the possibilities to create dynamic content within a webserver
- see that you don't have to implement a webserver to be able to serve dynamic content
- understand some main issues like blocking I/O that one should keep in mind when doing server side programming
- see how the web server is the entry point for web applications
- whitelisting of input vs blacklisting and a method of preventing XSS
- understand the basics of HTTP POST requests
- become aware of security issues while transfering data to a web server
- be able to create a simple web form in HTML
- See how a POST request is handled in a Java Servlet
- get to know the Request object
- see how a data base query and more advanced technology can be included to a servlet
- understand how javascript was supposed to support people to fill out web forms
- understand the issues and disadvantages that arise with javascript
- be aware of JavaScript APIs
- know some of the standard JavaScript libraries
- be able to understand the concept of Ajax requests.
Discussion
Web Science/Part2: Emerging Web Properties
Lessons
- The question will remain unanswered during the lesson and the entire course.
- question of size is underspecified because a measure is needed.
- measure depends heavily on the choice of how we model the web.
- We have not yet defined what we mean when we say World Wide Web.
- The web as a software system.
- The web as a collection of text documents.
- The web as a graph of interlinked documents.
- Even when choosing 1 point of view we have fundamentally different ways of modelling.
- understand that only the model is described.
- description of the model can be used for interpretation.
- within the descriptive model one chooses measures to describe the object of study.
- understand the notion of a modelling choice
- be able to criticise a descriptive model and the modelling choices
- Can be used to try to give a reason why something works.
- need to be run more than once!
- understand the notion of a modeling parameter
- will be compared to the descriptive model of our object of study.
- Understand why we selected simple English Wikipedia as a toy example for modeling the web
- Understand that a task already as simple as counting words includes modeling choices
- Be familiar with the term “unique word token”
- Know some basic tools to count words and documents
- Be familiar with some basic statistical objects like Median, Mean, and Histograms
- Should be able to relate a histogram to its cumulative distribution function
- Understand the ongoing, cyclic process of research
- Know what falsifiable means and why every research hypothesis needs to be falsifiable
- Be able to formulate your own research hypothesis
- Understand what a log-log plot is
- Improve your skills in reading and interpreting diagrams
- Know about the word rank / frequency plot
- Should be able to transfer a histogram or curve into a cumulative distribution function
- Get a feeling for interdisciplinary research
- Know the Automated Readability Index
- Have a strong sense of support for our research hypothesis
- Be able to critically discuss the limits of our models
- Be able to name some fundamental properties about how frequencies of words in texts are distributed
- Be a little bit more cautious about visual impressions when looking at log-log plots
- Know both formulations of Zipf’s law
- Be able to do a coordinate transformation to change the scales of your plots
- Understand in which scenario power functions appear as straight lines
- Know in which scenarios exponential functions appear as straight lines
- Be even more cautious about your visual impressions
- Know the axioms for a distance measure and how they relate to norms.
- Know at least two distance measures on functions spaces.
- Understand why changing to the CDF makes sense when looking at distance between functions.
- Understand the principle of the Kolomogorov-Smirnov test for fitting curves
- Know how to transform a rank frequency diagram to a powerlaw plot.
- Understand how powerlaw and pareto plots relate to each other.
- Be able to explain why a pareto plot is just and inverted rank frequency diagram
- Be able to transform the zipf coefficient to the powerlaw and pareto coefficient and vice versa.
- Understand that building the CDF is basically like building the integral.
- Know the properties of a similarity measure
- Be able to relate similarity and distance measures
- Know of two applications for modelling similarity
- Understand how text documents can be modeled as sets
- Know the Jaccard coefficient as a similarity measure on sets
- Know a trick how to remember the formula
- Be aware of the possible outcomes of the Jaccard index
- As always be able to criticize your model
- Be familiar with the the vector space model for text documents
- Be aware of term frequency and (inverse) document frequency
- Have reviewed the definitions of base and dimension
- Realize that the angle between two vectors can be seen as a similarity measure
- Be aware of a unigram Language Model
- Know Laplacian (aka +1) smoothing
- Know the query likelihood model
- The Kullback Leibler Divergence
- See how a similarity measure can be derived from Kullback Leibler Divergence
- Understand that different modeling choices can produce very different results.
- Have a feeling how you could statistically compare the differences of the models.
- Know how you could extract keywords from documents with the tf-idf approach.
- Try to argue which model you like best in a certain scenario.
- Understand the principle methodology for building generative models
- Remember why people are interested in generative models
- Know why descriptive models are needed when evaluating a generative model
- Be aware of one way to create a model for text generation
- Understand how to sample values from an arbitrary probability distribution
- Have seen yet another application of the cumulative distribution function
- Understand that sampling from a distribution is just a coordinate transformation of the uniform distribution
- See that it makes sense to compare statistics
- Understand that comparing statistics is not a well defined task
- Be aware of the fact that very different models could lead to the same statistics
- See that one can always increase the model parameters
- Know that increasing model parameters often yields a more accurate model
- Be aware of the bigram and mixed models as examples for our generative processes
- Be familiar with a set theoretic way of denoting a graph
- Know at least 4 different types of graphs
- Have practiced your abilities in reading and writing mathematical formulas
- Be able to model web pages as a graph
- Know that the authorship graph is bipartite
- Know what kind of graph the graph of web pages is
- (as always) be aware of the fact that modeling is done by making choices
- Know terms like Size and (unique) volume
- Be able to count the in and out degree of web pages
- Have an idea what kind of law (in & out) degree distributions follow
- Know that degree is not distributed in a fair way
- Know that the Gini coefficient can be used to measure fairness
- Understand the notion of a path in a (directed) graph
- Know that shortest paths between nodes need not be unique
- Understand the notion of a strongly connected component
- Know about the diameter of a graph
- Be aware of the bow tie structure of the Web
- Be able to read and build an adjacency matrix of a graph
- Know some basic matrix vector multiplications to generate some statistics out of the adjacency matrix
- Understand what is encoded in the components of the k-th power of the Adjacency matrix of a graph
