jh27 / inst737

ML project

This is for class project in INST737.

Data source

source: https://data.stackexchange.com

Brief explanation of database is here: https://meta.stackexchange.com/questions/2677/database-schema-documentation-for-the-public-data-dump-and-sede

Example data files to work with

For project ideatons, please refer to the example files (.csv). The brief description of each file can be found as below:

• posts

Contains information of each post (a thread of a question & answer(s))

• Users

Contains information of each user in Stack Overflow

• Comments

Contains information of each comment attached to either a question or an answer

• Badges

Contains information of each badge awarded to a user for the one's contribution to the site

• Tags

Contains information of each tag associated with a post. A post may have multiple tags.

These datasets are taken from Stack Overflow only.

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Below are the list of papers that you might find helpful for brainstorming.

Reference papers

• ICWSM2017
• Min(e)d Your Tags: Analysis of Question Response Time in StackOverflow https://pdfs.semanticscholar.org/312d/a6ff7dc3aa104493e3c8e7be8313020f16bd.pdf

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• Discovering values~~ =======
• From the paper titled: Discovering values~~~

27 features used

95d0fd8e19aeab79133bff6370915452339cb747

Questioner features (SA), 4 features total: questioner repu- tation, # of questioner’s questions and answers, questioner’s percentage of accepted answers on their previous questions.

Activity and Q/A quality measures (SB ), 8 features total: # of favorites, # of page views, # positive and negative votes on question, # of answers, maximum answerer reputation, high- est answer score, reputation of answerer who wrote highest- scoring answer,

Communityprocessfeatures(SC),8featurestotal:average answerer reputation, median answerer reputation, fraction of sum of answerer reputations contributed by max answerer reputation, sum of answerer reputations, length of answer by highest-reputation answerer, # of comments on answer by highest-reputation answerer, length of highest-scoring an- swer, # of comments on highest-scoring answer.

Temporal process features (SD), 7 features total: average time between answers, median time between answers, min- imum time between answers, time-rank of highest-scoring answer, wall-clock time elapsed between question creation and highest-scoring answer, time-rank of answer by highest- reputation answerer, wall-clock time elapsed between ques- tion creation and answer by highest-reputation answerer.

NLP analyses examples

For text summarization&classification

-Extracting Sentence Segments for Text Summarization: A Machine Learning Approach https://dl.acm.org/citation.cfm?id=345566

-BOOK: Learning to Classify Text Using Support Vector Machines: Methods, Theory, and Algorithms https://dl.acm.org/citation.cfm?id=1105708

-Thumbs up?: sentiment classification using machine learning techniques https://dl.acm.org/citation.cfm?id=1118704

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Other NLP analyses (not in papers, but in articles or other sources)

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Other NLP analyses (not in papers, but in articles or other sources)

95d0fd8e19aeab79133bff6370915452339cb747

1. 2015 presidential debate link

2. Topic modeling of Stack Overflow questions link

General ML methods / Techniques

• Which algorithm to solve my problem? link

Stack OVerflow papers

• Toward Understanding the Causes of Unanswered Questions in Software Information Sites: A Case Study of Stack Overflow

• Fit or Unfit : Analysis and Prediction of ‘Closed Questions’on Stack Overflow

• Answering questions about unanswered questions of Stack Overflow