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# g0v event participation analysis project 2022

On occasion of g0v’s 10th anniversary in fall 2022, Jothon invited Tilman to conduct a quantitative analysis of participation in the over 120 g0v Taiwan events held during this decade (hackathons, summits, and smaller topic-specific events like infrathons), which were attended by over 4000 people.

This project has three main goals:

## Provide data to a new credential system for g0v community members
gov/jothon is preparing a badge system to enable people to publicly display their participation in g0v, based on activity levels in various collaboration platforms used by the community, and at g0v events. (This will use thresholds such as having made a minimum number of edits on HackMD, having posted a minimum number of times in a g0v Slack channel, or having registered for a minimum number of g0v hackathon events.)

See https://g0v.hackmd.io/egkNjY94QfqC8DlN1AzM-g for documentation of this badge system project, including its privacy precautions.

To this badge system, the event participation analysis project will contribute the number of g0v events that a particular participant has registered for, possibly in some variations such as limiting it to a particular type of events, or (for movement "elderly") a certain number of years ago. No information about this number will be published, unless the participant chooses to make it public by requesting their badge.

## Impact analysis: Quantify overall g0v event participation and trends
To help understand the size and nature of g0v's impact, and how it has developed since 2012, this project is conducting aggregated data analysis of event registration data to answer questions about metrics such as:
- the number of g0v event registrations per year since 2012
- estimating the total number of people who have ever attended a g0v event
- the ratio of new vs. recurring participants at g0v hackathons

## Analysis of participant interests, event participation dynamics and event logistics questions

At most g0v events, attendees have been asked to answer various survey-type questions, e.g. multiple-choice questions about their occupation and free-form questions on "key words" that they chose to describe their interests and specialties to other attendees (e.g. "Python","法律", "設計"). We are conducting an aggregate analysis of this data, which among other things may support a more in-depth understanding of how "technical" and “non-technical” people come together at g0v.

To support a better understanding how and why people join and stay in the g0v community, this project is conducting aggregate analysis of e.g.:
- first-time attendees (see also part 2 "impact analyis", above)
- retention (e.g.: how likely are people to attend another g0v event after their first one)

This part of the project may also involve comparison with some recent voluntary post-event surveys that have been analyzed separately.

This part of the project will also touch some logistics related questions that may help inform future organizing work, such as
- the typical distribution of registrations over time relative to the event start date
- the percentages of participants who request lunch or vegetarian lunch

## Project personnel
The study is conducted by Tilman in collaboration with the g0v jothon taskforce. Tilman has a master's degree in information and data science from the UC Berkeley School of Information and over half a decade of experience as product data analyst and data scientist, including at the Wikimedia Foundation (the nonprofit that runs Wikipedia).

## Privacy and security
The study is based on the registration data for g0v events that KKTIX (the service g0v/jothon/g0v summit) have been using for this purpose since 2012) stores under [their privacy policy](https://kktix.com/policy) and makes accessible to a small number of trusted users from g0v/jothon who are involved with event organizing. In order to conduct the analysis, the relevant event datasets are exported from KKTIX’s servers and temporarily stored locally in encrypted form. Only the researcher (Tilman) has access to these copies, which will be deleted no later than 90 days after the analysis has been published. Tilman has signed a data protection confidentiality letter acknowledging the obligation to keep all confidential data secret and protected, and comply with applicable laws.

Except for the contribution to the g0v credential system described above, only aggregate results will be released to the public, in a form that does not allow de-anonymization or other conclusions about individual participants.

## Communication / contact
For questions about the project, feel free to contact @Tilman on the g0v Slack or email him ("haebwiki" at a certain large freemail service run by Google). In July 2022, an early version of this project and the badge credentials idea was presented for discussion at infrath20n ([meeting notes](https://g0v.hackmd.io/jnOojcnRRoeQQ8VY8oByew?view)). It is also planned to present the in-progress project again at an upcoming g0v infrathon for feedback before finalizing results.

## Data access
- 2022/9/21 `chihao` added `Tilman` to the kktix org `g0v-summit-2020` as an `Analyst` (access to Attendee Information)