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Steam Hype

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This repository contains Python code to find upcoming Steam games with many followers.

Requirements

  • Install the latest version of Python 3.X.
  • Install the required packages:
pip install -r requirements.txt

Usage

As of November 2020, SteamHype.com is down. Please refer to this Colab notebook to rely on SteamDB. Open In Colab

Alternatively:

python compare_to_top_wishlists.py

or:

import compare_to_top_wishlists

compare_to_top_wishlists.main(version=2)

Previously, when SteamHype.com was up, usage was as follows.

To download data:

python download_hype.py

To print formatted output:

python utils.py

To compare top followed games to top wishlisted games:

import compare_to_top_wishlists

compare_to_top_wishlists.main(version=1)

Results

Results are shown on the Wiki.

The rank-order correlation between the top followed games (depth=166) and the top wishlisted games is positive:

As of November 2020, using SteamDB's hype (depth=250), as SteamHype.com is down:

  • Spearman rho coefficient ~ 0.44
  • Kendall's tau coefficient ~ 0.33
  • Weighted Kendall's tau coefficient ~ 0.64
  • Average overlap ~ 66.5%
  • Rank-biased overlap ~ 68.0%

References