yijingch / reddit-toxicity

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Toxicity at scale?

A structural view of conversation quality in political subreddits

Class project repository:

  • DNDS 6014: Introduction to Computational Social Science
  • DNDS 6291: Statistical Methods in Network Science

Research questions

Overarching RQ: Where and how do toxic conversations happen online?

(A) User-level:

  • A1: Who talks toxically?
  • A2.1: Are my neighbors generally more toxic than me (i.e., toxicity friendship paradox)?
  • A2.2: Does the TFP (if any) persist over time?

(B) Submission-level:

  • B1: How do toxic conversations usually structure?
  • B2: How do toxic conversations unfold?

Code guide

  • pipeline-reddit-fixstart-by-year.py: crawl Reddit submissions and comments through Pushshift API
  • parse-to-db.py: parse .json files to sqlite .db
  • select-user.py: write lists of active users for future subsetting in analysis
  • basic-descriptives.ipynb: produce basic descriptives of the entire dataset
  • user-level-static.ipynb: answers A1 and A2.1
  • user-level-tfp-overtime.ipynb: answers A2.2
  • subm-level.ipynb: answers B1 and B2
  • utils.py: basic utility functions such as importing data and building networks

Dataset

User-generated content retrieved from 51 active political subreddits from Jan 2012 to Dec 2015.

  • 1.4m+ submissions
  • 20m+ comments
  • 900k+ unique users

Ethics and privacy concerns of dataset collection/management:

  • Collected through Pushshift API
  • Analyzed/discussed only in the academic setting
  • Personally identifiable information is either aggregated or anonymized.
  • Raw data or text content will not be released here.

Reference

[1] Eom, Y. H., & Jo, H. H. (2014). Generalized friendship paradox in complex networks: The case of scientific collaboration. Scientific reports, 4(1), 1-6.

[2] Goel, S., Anderson, A., Hofman, J., & Watts, D. J. (2016). The structural virality of online diffusion. Management Science, 62(1), 180-196.

[3] Rajadesingan, A., Resnick, P., & Budak, C. (2020, May). Quick, community-specific learning: How distinctive toxicity norms are maintained in political subreddits. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 14, pp. 557-568).

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