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Bewelcome.org -- a non-profit democratic hospex service set up for growth

Rustam Tagiew

TL;DR

This study analyzes Bewelcome.org as a representative non-profit hospex platform and compares its dynamics to Hospitality Club and Couchsurfing using BW-derived data, Google Trends, and mirrored CS data. It employs data-driven methods (correlations, Box-Cox transformations, and power-function fits) to model growth, engagement, and migration patterns, highlighting the strong link between online interest and signups and the historical HC→CS shift. The findings reveal BW-specific engagement metrics, messaging-driven activation, and a sizable but evolving community, all within the constraints of limited CS data access. The work yields practical insights for growing traveler participation and estimating community size in data-restricted environments, with implications for platform strategy and policy.

Abstract

This paper presents an extensive data-based analysis of the non-profit democratic hospitality exchange service bewelcome.org. We hereby pursuit the goal of determining the factors influencing its growth. It also provides general insights on internet-based hospitality exchange services. The other investigated services are hospitalityclub.org and couchsurfing.org. Communities using the three services are interconnected -- comparing their data provides additional information.

Bewelcome.org -- a non-profit democratic hospex service set up for growth

TL;DR

This study analyzes Bewelcome.org as a representative non-profit hospex platform and compares its dynamics to Hospitality Club and Couchsurfing using BW-derived data, Google Trends, and mirrored CS data. It employs data-driven methods (correlations, Box-Cox transformations, and power-function fits) to model growth, engagement, and migration patterns, highlighting the strong link between online interest and signups and the historical HC→CS shift. The findings reveal BW-specific engagement metrics, messaging-driven activation, and a sizable but evolving community, all within the constraints of limited CS data access. The work yields practical insights for growing traveler participation and estimating community size in data-restricted environments, with implications for platform strategy and policy.

Abstract

This paper presents an extensive data-based analysis of the non-profit democratic hospitality exchange service bewelcome.org. We hereby pursuit the goal of determining the factors influencing its growth. It also provides general insights on internet-based hospitality exchange services. The other investigated services are hospitalityclub.org and couchsurfing.org. Communities using the three services are interconnected -- comparing their data provides additional information.

Paper Structure

This paper contains 6 sections, 8 figures, 1 table.

Table of Contents

  1. Introduction
  2. Terminology
  3. Related Work
  4. General development of hospex services
  5. Insights for BW
  6. Conclusion

Figures (8)

  • Figure 1: High linear correlation of .971 between Google search volume for ,, Couchsurfing“ and CS monthly signup in the years 2005--2011 allows linear prediction for the subsequent development.
  • Figure 2: Google search volume for HC, CS and HC+CS. Pie chart of growth adjusted mean distribution of Google search for HC+CS over months.
  • Figure 3: Power function fits for CS total signup in Jan 2004 - Aug 2011 and in Aug 2009 - Aug 2011. Monthly CS signup deviation from its seasonalized power function fit as gray curve.
  • Figure 4: Domain name categorization and corresponding histogram in absolute numbers.
  • Figure 5: BW growth and 'no login' rate.
  • ...and 3 more figures