{"success":true,"last_page":true,"current_cursor":"*","next_page_cursor":"AoIIP7bZ8CtTb2Z0d2FyZSAxMg==","next_rank":5,"result_set_html":"  \u003cli class=\"search-result\" data-rank=\"1\"\n    \u003e\u003cdiv data-assignment_group-id=\"71\" class=\"assignment_group vertical-result-data index-entry\"\u003e\n  \u003ca href=\"/assignment_groups/71\" \n  data-assignment_group-id=\"71\"\u003e\u003cspan class=\"name\"\u003eA comparison of authors writing using text analysis\u003c/span\u003e\u003c/a\u003e\n\n  \u003cspan class=\"metadata\"\u003e\n    \u003cspan class=\"author\"\u003eHank Feild\u003c/span\u003e \n    \u0026mdash;\n    \u003cspan class=\"added-by\"\u003eAdded on June 03, 2019 by hfeild\u003c/span\u003e \n  \u003c/span\u003e\n\n  \u003cspan class=\"summary\"\u003eStudents write a report comparing the writing of two authors using word unigram and bigram analysis and submit a Jupyter Notebook showing the code used to extract the data used in the analysis.\u003c/span\u003e\n\n\n    \u003cspan class=\"version-header\"\u003eVersions:\u003c/span\u003e\n    \u003cdiv class=\"assignments-list\"\u003e\n      \u003cdiv data-assignment-id=\"68 class=\"assignment-entry\"\u003e \n          \u003ca href=\"/assignment_groups/71/assignments/68\"\u003e\u003cspan class=\"assignment-course\"\u003eCSC440—Data Mining \u0026amp; Visualization\u003c/span\u003e\u003c/a\u003e\n          (\u003cspan class=\"instructor\"\u003eFeild\u003c/span\u003e,\n          \u003cspan class=\"date\"\u003eSpring 2019\u003c/span\u003e)\n      \u003c/div\u003e\n    \u003c/div\u003e\n\n  \u003cspan class=\"metadata\"\u003e\n\n    \u003cspan class=\"fields-of-study\"\u003eField of study: Computer Science\u003c/span\u003e\u003cbr/\u003e\n\n    \u003cspan class=\"tags\"\u003e\n\u003cdiv class=\"tag-badge\"\u003e\n  \u003ca href=\"/tags/56\"\u003etext analysis\u003c/a\u003e (12)\n  \n\u003c/div\u003e\n\u003c/span\u003e\n  \u003c/span\u003e\n\u003c/div\u003e\n\u003c/li\u003e\n  \u003cli class=\"search-result\" data-rank=\"2\"\n    \u003e\u003cdiv data-assignment_group-id=\"69\" class=\"assignment_group vertical-result-data index-entry\"\u003e\n  \u003ca href=\"/assignment_groups/69\" \n  data-assignment_group-id=\"69\"\u003e\u003cspan class=\"name\"\u003eFitting probability models for Author detection\u003c/span\u003e\u003c/a\u003e\n\n  \u003cspan class=\"metadata\"\u003e\n    \u003cspan class=\"author\"\u003ePhil Lombardo\u003c/span\u003e \n    \u0026mdash;\n    \u003cspan class=\"added-by\"\u003eAdded on May 20, 2019 by plombardo\u003c/span\u003e \n  \u003c/span\u003e\n\n  \u003cspan class=\"summary\"\u003eUsing a custom python script and google colab, students extract word frequencies from raw text files on Project Gutenberg and analyze them in an attempt to identify an mystery author.\u003c/span\u003e\n\n\n    \u003cspan class=\"version-header\"\u003eVersions:\u003c/span\u003e\n    \u003cdiv class=\"assignments-list\"\u003e\n      \u003cdiv data-assignment-id=\"66 class=\"assignment-entry\"\u003e \n          \u003ca href=\"/assignment_groups/69/assignments/66\"\u003e\u003cspan class=\"assignment-course\"\u003eMTH225—Probability\u003c/span\u003e\u003c/a\u003e\n          (\u003cspan class=\"instructor\"\u003eLombardo\u003c/span\u003e,\n          \u003cspan class=\"date\"\u003eFall 2018\u003c/span\u003e)\n      \u003c/div\u003e\n    \u003c/div\u003e\n\n  \u003cspan class=\"metadata\"\u003e\n\n    \u003cspan class=\"fields-of-study\"\u003eField of study: Mathmatics\u003c/span\u003e\u003cbr/\u003e\n\n    \u003cspan class=\"tags\"\u003e\n\u003cdiv class=\"tag-badge\"\u003e\n  \u003ca href=\"/tags/88\"\u003eauthor detection\u003c/a\u003e (1)\n  \n\u003c/div\u003e\n\n\u003cdiv class=\"tag-badge\"\u003e\n  \u003ca href=\"/tags/47\"\u003epython\u003c/a\u003e (4)\n  \n\u003c/div\u003e\n\n\u003cdiv class=\"tag-badge\"\u003e\n  \u003ca href=\"/tags/56\"\u003etext analysis\u003c/a\u003e (12)\n  \n\u003c/div\u003e\n\u003c/span\u003e\n  \u003c/span\u003e\n\u003c/div\u003e\n\u003c/li\u003e\n  \u003cli class=\"search-result\" data-rank=\"3\"\n    \u003e\u003cdiv data-dataset-id=\"11\" class=\"dataset vertical-result-data index-entry\"\u003e\n\n  \u003cspan class=\"name\"\u003e\u003ca href=\"/datasets/11\"\u003eAuthorship Detection with Authors from Project Gutenberg\u003c/a\u003e\u003c/span\u003e\n\n  \u003cspan class=\"summary\"\u003eA folders containing raw text files to use for Authorship detection.\u003c/span\u003e\n\n  \u003cspan class=\"metadata\"\u003e\n    \u003cspan class=\"date\"\u003eAdded on May 20, 2019 by plombardo\u003c/span\u003e\n    \u0026mdash;\n\n    \u003cspan class=\"used-in\"\u003eUsed in 1 assignment and 1 example\u003c/span\u003e\u003cbr/\u003e\n    \n    \u003cspan class=\"tags\"\u003e\n\u003cdiv class=\"tag-badge\"\u003e\n  \u003ca href=\"/tags/89\"\u003eplain text book\u003c/a\u003e (2)\n  \n\u003c/div\u003e\n\n\u003cdiv class=\"tag-badge\"\u003e\n  \u003ca href=\"/tags/47\"\u003epython\u003c/a\u003e (4)\n  \n\u003c/div\u003e\n\n\u003cdiv class=\"tag-badge\"\u003e\n  \u003ca href=\"/tags/56\"\u003etext analysis\u003c/a\u003e (12)\n  \n\u003c/div\u003e\n\u003c/span\u003e\n  \u003c/span\u003e\n  \n\u003c/div\u003e\u003c/li\u003e\n  \u003cli class=\"search-result\" data-rank=\"4\"\n    \u003e\u003cdiv data-software-id=\"12\" \n  class=\"software vertical-result-data index-entry\"\u003e\n\n  \u003cspan class=\"name\"\u003e\u003ca href=\"/software/12\"\u003eget-Tweets\u003c/a\u003e\u003c/span\u003e\n\n  \u003cspan class=\"summary\"\u003eA python script for downloading tweets based on searches or a user\u0026#39;s timeline.\u003c/span\u003e\n\n  \u003cspan class=\"metadata\"\u003e\n    \u003cspan class=\"date\"\u003eAdded on May 21, 2018 \n      by hfeild\n    \u003c/span\u003e\n    \u0026mdash;\n\n    \u003cspan class=\"used-in\"\u003eUsed in 1 \n      assignment and \n      0 \n      examples\u003c/span\u003e\u003cbr/\u003e\n\n    \u003cspan class=\"tags\"\u003e\n\u003cdiv class=\"tag-badge\"\u003e\n  \u003ca href=\"/tags/50\"\u003egithub\u003c/a\u003e (1)\n  \n\u003c/div\u003e\n\n\u003cdiv class=\"tag-badge\"\u003e\n  \u003ca href=\"/tags/47\"\u003epython\u003c/a\u003e (4)\n  \n\u003c/div\u003e\n\n\u003cdiv class=\"tag-badge\"\u003e\n  \u003ca href=\"/tags/49\"\u003esocial media\u003c/a\u003e (2)\n  \n\u003c/div\u003e\n\n\u003cdiv class=\"tag-badge\"\u003e\n  \u003ca href=\"/tags/3\"\u003esocial networks\u003c/a\u003e (4)\n  \n\u003c/div\u003e\n\n\u003cdiv class=\"tag-badge\"\u003e\n  \u003ca href=\"/tags/48\"\u003etwitter\u003c/a\u003e (3)\n  \n\u003c/div\u003e\n\u003c/span\u003e\n  \u003c/span\u003e\n  \n\u003c/div\u003e  \u003c/li\u003e\n"}