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Deliver 4 milestones towards 1 model to understand the diffusion of content on the Wikimedia projects
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Description

This task reunites our efforts in modeling content diffusion in Wikipedia.

Goals by Quarter:

  • Q1 Milestone 1: Prepare the datasets for training 2 models about diffusion of content. (T252933)
  • Q2 Milestone 2: Train and validate 1 model: predict the likelihood of an item spreading from a given project to another; (T252933]
  • Q3 Milestone 3: Train and validate a second model to predict the likelihood of a project receiving information from another project.
  • Q4 Milestone 4: Publish the work and share insights from the research with the Wikimedia community.

Links to:
Paper: https://arxiv.org/abs/2103.16613
Code: https://github.com/rodolfovalentim/wikipedia-content-propagation
Meta: https://meta.wikimedia.org/wiki/Research:Exploration_on_content_propagation_across_Wikimedia_projects
Dataset: https://zenodo.org/record/4433137

Event Timeline

Updates

  • The two datasets have been prepared:
    • One dataset with items that propagates across Wikipedias, removing bot activity.
    • Another dataset about external references (links) across projects.

Updates

  • The dataset are ready. We are waiting for the paper to be published to share the link in public. Currently, the datasets are available under request via email.

Updates

  • Depending on the results for the paper submission (received border line evaluation), we are planning to publish the dataset separately from the model. In the case of publishing the dataset separately, this will be done during Q3.

Updates

  • We submitted the propagation dataset to ICWSM.
  • We are building a new model considering content popularity (pageviews).

Updates

  • The dataset to model content propagation has been published in Zenodo.

Updates

  • New experiments using pageviews as feature to predict content propagation.

Updates

  • Pageviews added an improvement over %5 on predicting content propagation.
  • We are currently working on add content-related information (articles meta-data) to de model. This will allow to study the effects content quality on the spread patterns.

Updates

  • We are improvements on the model to predict the next language of propagation.
  • We are working on modeling changes of content propagation behavior depending on the article reliability.

Update

  • The paper with the dataset and first model has been accepted on ICWSM'21
  • We are working on the camera ready version.

Update

  • Finishing the camera ready version for ICWSM'21 paper.
  • We have trained a new model, content information, to predict the likelihood of item to propagate to other projects.
  • We are working on documenting our new results.

*Update*

  • Preparing the ICWSM presentation.

Updates

  • The work is published, poster and presentation submitted.

Updates

  • We will be presenting this work at ICSWM, on June 10th.

Updates

  • The paper was successfully presented at ICWSM'21.
  • We also shared this and the "Wiki-Reliability" paper on the wiki-research mailing list.

With these last two updates, we have finalized this task.

diego updated the task description. (Show Details)