README

--There is the list of code files. Description are under file names.
--The reference means the methodologies and results of this file are mentioned in these sections on the thesis.

-Procedure: Data Collection-
Step 1_Project_Topic Analysis .ipynb
	Find topics from suspended data (reference: 4.2.2, 5.2.1 and 5.3.1).
Step 2_Data Collection (China) .ipynb
	Daily work on collecting unsuspended data on Chinese topics (reference: 4.2.2).
Step 2_Data Collection (Russia) .ipynb
	Daily work on collecting unsuspended data on Russian topics (reference: 4.2.2).

-Procedure: Feature Production-
Step 3_Sentimental Analysis .ipynb
	Analysis the sentiment of tweets (reference: 4.3, 5.2.2 and 5.3.2).
Step 4_Hashtags .ipynb
	Find hashtags relative features (reference: 4.3, 5.2.3 and 5.3.3).
Step 5_Day & Sorting .ipynb
	Split time data into day, hour and minute (reference: 4.3).

-Procedure: Feature selection-
Step 6_Feature Selection .ipynb
	Select feature combination by three approaches (reference: 4.4, 5.2.4 and 5.3.4).

-Procedure: Classifier and Analysis-
Step 7.1_Classifier (China) - by classifier.ipynb
	Select models by classifier performance and analyse results on Chinese topics (reference: 4.5 and 5.2.5.1).
Step 7.1_Classifier (China) - by classifier.ipynb
	Select models by classifier performance and analyse results on Russian topics (reference: 4.5 and 5.3.5.1).
Step 7.2_Classifier (China) - by combination.ipynb
	Select models by combination performance and analyse results on Chinese topics (reference: 4.5 and 5.2.5.2).
Step 7.2_Classifier (China) - by combination.ipynb
	Select models by combination performance and analyse results on Russian topics (reference: 4.5 and 5.3.5.2).
Step 8.1_Aanlysis by classifier.ipynb
	Analytic work on Step 7.1 (reference: 4.5, 5.2.5.1 and 5.3.5.1).
Step 8.2_Aanlysis by models.ipynb
	Analytic work on Step 7.2 (reference: 4.5, 5.2.5.2 and 5.3.5.2).