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PyStack: Powerful Python Toolkit for Analyzing Stack Exchange Sites

This tooklit provides several useful Python scripts for processing stack exchange data dump

Requirements

• Python 2.7
• pandas
• xml.etree.ElementTree
• cPickle or pickle

PyStack

Usage

• download your interested Stack Exchange site data (*.stackexchange.com.7z) from stack exchange data dump, such as ai.stackexchange.com.7z
• unzip ai.stackexchange.com.7z to directory: dataset/ai
• cd pre_precessing
• execute: python pystack.py --input ../dataset/ai/ --task all

Parameters of pystack.py

• input: file directory which saves Posts.xml, PostLinks.xml, Votes.xml, Badges.xml, and Comments.xml. In above example, input is dataset/ai
• task: can be selected from [Posts, PostLinks, Votes, Badges, Comments, and All], Each task corresponding a python file. By default, task is set as all.

Outputs of pystack.py

• Outputs will be saved in corresponding .csv and .pkl.
• Analysis/Statistics of the Stack Exchange Site will be saved in file pystack_analysis.log.
• We will describe the details in each task individually.

Process Posts.xml

Usage

python process_posts.py --input ../dataset/ai/Posts.xml

OR

python pystack.py --input ../dataset/ai/ --task Posts

Output

• QuestionId_AskerId.csv
• QuestionId_AnswererId.csv
• QuestionId_AcceptedAnswererId.csv
• AnswerId_QuestionId.csv
• AnswerId_AnswererId.csv
• AskerId_AnswererId.csv
• question_tags.pkl: A dict pickle file, of which key is question id, and its value is a list of tags
• Questions.pkl: A dict pickle file, of which key is question id, and its value is a list of [question title, question body]
• Answers.pkl: A dict pickle file, of which key is answer id, and its value is corresponding body

Process PostLinks.xml

Usage

python process_postlinks.py --input ../dataset/ai/PostLinks.xml

OR

python pystack.py --input ../dataset/ai/ --task PostLinks

Output

• PostId_RelatedPostId.csv: PostId -> RelatedPostId if LinkTypeId = 1; PostId is a duplicate of RelatedPostId if LinkTypedId = 3
• Duplicate_Questions.csv: Duplicate question pairs
• Related_Questions_Source2Target.csv: There is a link from a souce question to a target question

Process Votes.xml

Usage

python process_votes.py --input ../dataset/ai/Votes.xml

OR

python pystack.py --input ../dataset/ai/ --task Votes

Output

• QuestionId_Bounty.csv: columns = ["QuestionId","Bounty"], index = False

Process Badges.xml

Usage

python process_badges.py --input ../dataset/ai/Badges.xml

OR

python pystack.py --input ../dataset/ai/ --task Badges

Output

• Badges.csv, columns = ["UserId","BadgeName","BadgeDate"], index = False

Process Comments.xml

Usage

python process_comments.py --input ../dataset/ai/Comments.xml

OR

python pystack.py --input ../dataset/ai/ --task Comments

Output

• PostId_CommenterId.csv: index = False, columns = ["PostId","UserId","Score"], UserId gave a comment on PostId (Question or Answer(?)). And the number of up-votes he/she get is Score
• PostId_CommenterId_Text.pkl: d = {"PostId":[],"UserId":[],"Score":[],"Text":[],"CreationDate":[]}

Questions

How to unzip a *.7z file

• Install p7zip if not already installed: sudo apt-get install p7zip
• To install the command line utility sudp atp-get install p7zip-full
• Or Install p7zip on Mac OSX
• execute command to extract a *.7z file: 7za x *.7z

Discuss

This code is written for research. It aims to help you start to do your analysi on Stack Exchange Sites without the dirty preprocessing work.

Feel free to post any questions or comments.

Citation

If you use this code, please consider to cite QDEE: Question Difficulty and Expertise Estimation in Community Question Answering Sites and ColdRoute: effective routing of cold questions in stack exchange sites