User:Renepick/helpfull links


 * A lot of graphics can be generated with software from Social_network_analysis_software we used: http://graph-tool.skewed.de/static/doc/generation.html
 * the graph simulation tool (net logo) can be used to visualize graphs and demonstrate graph network growth: http://ccl.northwestern.edu/netlogo/docs/programming.html
 * Lua Help on wikipedia
 * gadgets (for deployting java script)

thoughts on web structure

 * better motivate why to start with links on the web example (one of the well understood problems and still a rather simple and easy to understand problem)
 * this is true, but there is even more to link creation: it is the simplest Web content creation activity that delineates the Web 1.0 from everything else. Before the Web, people already wrote documents (and one could observe Zipf distributions, like Zipf did in the 30ies/40ies) - there is nothing more basic to Web content than creating links between documents
 * why talking about predictive and describtive models? Is the goal of web science to find as many models as possible which are predictive and descriptive?
 * exercise: define research questions that relate to model creation on the web.
 * micro / macro :
 * if we have a model for micro we can compare our model with the reality and do stuff like precision recall
 * if we have a macro model we can obtain statistics of the reality and compare them to statistics of our model
 * really go in here and have the two opposing ways (in much more detail. How would you validate the quality of a micro model? Why cant we do micro models? What happens when we do macro models?)

==> the storyline could be.
 * 1) Introduce Statistical modeling (descriptive and predictive models)
 * 2) introduce the methodology of micro models (e.g. simulate and compare with reality) (do we have a simpler example than recommendations? Could we evenhave a recomender e.g. for blogger to create the next link)
 * 3) Introduce the methodology of macro models (e.g. simulate create aggregated statistics, also do aggregated stats fo the reallity and compare aggregated statistics.)

understanding statistical plots
explain what is displayed in the following diagram (focus on what is on the axis, what is the semantics of a single data point but also later on what does log log mean): Remark it is least important that everyone can say: "powerlaw / inverse polynomial" much more important is to understand what is plotted anyway.

also ask this question with a histogram plot

create a plot
Given the following graph: 1 2 1 3 2 1 2 3 2 4 3 2 3 4

What does the histogram look like? (choose from various diagrams)

counting
counting tfidf

comparing
indegree vs outdegree plots

related user

 * steffen on wikiversity and on commons
 * robs on wikiversity and on commons
 * rene on wikiversity and commons

to read

 * User:Rouslan.kv/law_copyright
 * User:Onse/Search_Engine_Ecosystem_part_2
 * User:Pavithrans/Copyright_and_Law_Seminar
 * User:Schin/Internet_Protocol
 * User:Rahul/Seminar_Topic
 * User:Oleamm/Search_engines_history_and_architecture