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A novel framework for learning latent information diffusion mechanism in online discussion forum

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NTPP: Nested Temporal Point Process

A nested point process in modeling social activities on online social forums, which is a a class that models the arrival in time of random events and their interaction with the state of a system.

This repository contains three components:

  • A comprehensive dataset of topic stream data and associated reply data from Reddit (retrieved by Pushshift API).
  • The full code of fitting and training all the parameters described in NTPP.py.
  • The adaptive simulation step of utilizing fitted parameters.

Dependencies

This code is written in Python. To use it you will need:

  • Numpy - 1.16.2
  • Scipy - 1.2.1
  • pandas - 0.23.4

It is recommended to use Anaconda since it includes all the Python-related dependencies

Usage

Data

The data used in this project can be downloaded from this link.

To produce the model-required Reddit data, one can also utilize Pushshift API to download Reddit threads and reply data in a given time range of different subforums.

Train Models

To train the model, try to run the ntpp.py.

python ntpp.py

Note that the parameter value ranges are hyper-parameters, and different range may result different performance in different dataset, be sure to tune hyper-parameters carefully.

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A novel framework for learning latent information diffusion mechanism in online discussion forum

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