{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# [NTDS'17] assignment 1: Feedback\n", "[ntds'17]: https://github.com/mdeff/ntds_2017\n", "\n", "[Effrosyni Simou](http://lts4.epfl.ch/simou), [EPFL LTS4](http://lts4.epfl.ch)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "**For the correction of the first assignment the following grading scheme was followed:**\n", "\n", "**1) find_connections function -> 20 points **\n", "\n", "Common mistakes included:\n", "* not using the Cursor object to iterate through pages\n", "* not accounting for protected users (if this was added in the network collection, points were removed only partially)\n", "\n", "** 2) collection of the Twitter network -> 30 points **\n", "\n", "Common mistakes included:\n", "* not handling protected users \n", "* not gathering different nodes in the first_nodes and the second_nodes list (only partial points extracted if the removal of duplicates was done efficiently in the next step)\n", "* adding protected users in the collected network and trying to recover their connections (not the best solution)\n", " \n", "\n", "**3) finding the total number of nodes (removing duplicates) -> 5 points**\n", "\n", "Common mistakes included:\n", "* Not removing at all existing duplicates\n", "* Removing only duplicates from first_nodes and second_nodes but not removing the duplicates of the nodes that were present in both of these lists\n", "\n", "**4) finding all of the inner connections between the collected nodes -> 20 points**\n", "\n", "Common mistakes included:\n", "* Simply adding the symmetric connections of the ones you had already found.\n", "* Only finding the inner connections between second nodes (remember that inner connections can exist also between two first nodes for instance)\n", "\n", "**5) construct adjacency matrix W from the dictionary ``network`` -> 10 points**\n", "\n", "Almost everyone did perfectly in this part.\n", "\n", "**6) Question 1 -> 1 point**\n", "\n", "Good answers from most in this part.\n", "\n", "**7) Plot of adjacency matrix W -> 1 point**\n", "\n", "Everyone did perfectly in this part.\n", "\n", "**8) Question 2 -> 3 points**\n", "\n", "Almost everyone did perfectly in this part.\n", "\n", "**9) Plot of degree distribution -> 1 point**\n", "\n", "OK answers from most at this part.\n", "\n", "**10) Question 3 -> 3 points**\n", "\n", "OK answers from most at this part.\n", "\n", "**11) Average degree -> 1 point**\n", "\n", "Everyone did perfectly in this part.\n", "\n", "**12) Question 4 -> 3 points**\n", "\n", "Common mistake:\n", "\n", "* Some people said that the diameter was 2.\n", "\n", "**13) Network pruning -> 2 points**\n", "\n", "Almost everyone did perfectly in this part." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Overall, very good job everyone! Keep up with the good work :)" ] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python [Root]", "language": "python", "name": "Python [Root]" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 1 }