/expert-influence

Modelling Experts Behaviour in Q&A Communities to Predict Worthy Discussion

Primary LanguageR

Modelling Experts Behaviour in Q&A Communities to Predict Worthy Discussion

Summary

This project is part of a scientific research. We are interested in knowing the influence of experts in discussions. You can find here the analysis of the paper "Modelling Experts Behaviour in Q&A Communities to Predict Worthy Discussions" published at the 17th IEEE International Conference on Advanced Learning Technologies - ICALT 2017. In other words, you will find here everything you need to reproduce this research. First, read the paper and then follow the instructions below.

Environment

Inserting data into MySQL

  • Open folder database/biology
  • Unzip bio-database.sql.zip
  • Run bio-database.sql

How did we extract the data?

We used the stackexchange API (http://api.stackexchange.com/docs/) to extract data from biology Q&A (http://biology.stackexchange.com/). Then, we loaded the data into MySQL.

Analysis

For the analysis, each one has a folder with the SQL that generated the CSV file. We used the CSV as the input for our R script.

A. Reputation and Participation Analysis

  • Open folder A
  • Execute: Rscript reputation.R

B. Quality of Interactions

  • Open folder B
  • Execute: Rscript qualityInteraction.R

C. Users Interactions and Evolution Analysis

  • Open folder C
  • Execute: Rscript evolution.R

D. Best Answers Analysis

  • Open folder D
  • Execute: Rscript best.R

E. Discussion Length Analysis

  • Open folder E/part-1
  • Execute: Rscript discussion.R
  • Open folder E/part-2
  • Execute: Rscript discussion.R

F. Graph and Correlation Analysis

  • Open folder F
  • Execute: Rscript graph.R

G. PREDICTIVE MODEL TO FINDING A WORTHY DISCUSSION

  • Open folder G/nnet
  • Execute: Rscript prediction-gbm.R
  • Open folder G/gbm
  • Execute: Rscript prediction-nnet.R