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# 授课计划

- 一、计算新闻传播学简介
- 二、大数据简介 (1h)
- 三、数据科学的编程工具:Python使用简介(3h)
- 四、数据抓取:抓取两会报告
- 五、数据抓取:抓取天涯论坛帖子
- 六、数据清洗:清洗推特数据
- 七、数据清洗:清洗占中新闻、清洗天涯论坛帖子
- 八、统计初步: 分析天涯论坛的帖子
- 九、机器学习: 分析天涯论坛的帖子
- 十、文本挖掘:简介
- 十一、文本挖掘:基于机器学习的情感分析
- 十二、文本挖掘:主题模型
- 十三、计算传播应用:推荐系统简介
- 十四、计算传播应用:推荐系统实践
- 十五、网络科学:理论简介
- 十六、网络科学:描述节点属性
- 十七、网络科学:分析网络结构
- 十八、课程总结与学生研究项目展示
- 一、[计算新闻传播学简介](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/01.intro2cjc.slides.html#) [[课程要求](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/0.about2cjc.slides.html#/)[常见问题](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/0.common_questions.slides.html#/)[Jupyter Notebook使用](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/01.jupyter notebook.slides.html#/)、 [Slides制作方法](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/01.slides.slides.html#/)]
- 二、[大数据简介 ](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/02.bigdata.slides.html#/)
- 三、[数据科学的编程工具:Python使用简介(3h)](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/03.python_intro.slides.html#/) [[Graphlab](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/03.graphlab.slides.html#/)[rpy2](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/03.rpy2.slides.html#/)]
- 四、数据抓取:[抓取政府工作报告](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/04.PythonCrawlerGovernmentReport.slides.html#/) [[Beautifulsoup](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/04.PythonCrawler_beautifulsoup.slides.html#/)]
- 五、数据抓取:[抓取天涯论坛帖子](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/05.PythonCrawler_tianya_threads.slides.html#/)
- 六、数据清洗:[清洗推特数据](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/06.data_cleaning_Tweets.slides.html#/)
- 七、数据清洗:[清洗占中新闻、清洗天涯论坛帖子](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/07.data_cleaning_occupy_central_news.slides.html#/)
- 八、统计初步: [分析天涯论坛的帖子](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/08.analyzing_tianya_thread_network.slides.html#/)
- 九、机器学习: [分析天涯论坛的帖子](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/09.machine_learning_with_sklearn.slides.html#/)
- 十、[文本挖掘简介](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/10.text_minning_gov_report.slides.html#/)
- 十一、文本挖掘:[基于机器学习的情感分析](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/11.sentiment_classifier.slides.html#/)
- 十二、文本挖掘:[主题模型](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/12.topic_models.slides.html#/) [[graphlab](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/12.topic-models-with-graphlab.slides.html#/)]
- 十三、计算传播应用:[推荐系统简介](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/13.recsys_intro.slides.html#/)
- 十四、计算传播应用:推荐系统实践 [[音乐推荐](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/14.millionsong.slides.html#/)[电影推荐](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/14.movielens_recommendation-systems.slides.html#/)[隐含语义模型](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/14.matrix-factorization-demo.slides.html#/)]
- 十五、[网络科学理论简介](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/15.network_science_intro.slides.html#/)
- 十六、[网络科学模型](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/16.network_science_models.slides.html#/)
- 十七、[网络科学:使用NetworkX分析网络结构](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/17.networkx.slides.html#/)
- 十八、课程总结 [[回帖网络分析](http://nbviewer.jupyter.org/github/computational-class/cjc2016/blob/gh-pages/slides/18.network analysis of tianya bbs.slides.html#/)]


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