Despite Wikipedia's objective of being a global encyclopedia, prior research has demonstrated that its content and sources do not adequately reflect the diversity of society. Various types of content gaps exist in Wikipedia. The gender content gap, in particular, has attracted much attention from the Wikipedia editor and research community. Specifically, the gender content gap is reflected in Wikipedia articles of women’s topics that (1) lack existence (e.g. Menking, 2017), (2) lack appropriate quality (including Neutral Point of View and completeness) (e.g. Morten Warncke-Wang, 2015), or (3) lack discoverability in relation to Wikipedia articles of men’s topics (e.g. Wagner, 2016).
Our goal is to use AI to promote gender diversity in Wikipedia contents, which will positively influence billions of people who use Wikipedia content directly, or indirectly through applications such as Google search engine.
The first step of the project is to interview stakeholders in the Wikipedia community to gain a community-grounded understanding of the gender gap. And the second step of the project is to develop an AI tool (similar to Cosley, 2007) that can give personalized editing recommendations to Wikipedia editors, which maximize editing power and help close the gender content gap.
Step 1: Understanding the gender content gap in Wikipedia community
To build a tool that solves real community issues, we would like to first gain a community-grounded understanding of the gender content gap. We would like to interview a diverse group of Wikipedia members (e.g. readers, editors, researchers) and learn about their perceptions and experiences related to the gender content gap.
We will reach out and recruit interview participants in ways consistent with the social norms of the Wikipedia community. For example, we will contact potential participants through relevant Wikiprojects' talk pages (listed below). We will also describe our study and post it in public forums in Wikipedia to (1) inform the community, (2) recruit more potential participants, and (3) present results of interview for more feedback. We have received IRB approval from the University of Minnesota for permission to conduct the research. Below, we will explain our interview plan in detail, our interview structure and interview questions.
Interview contact list
We plan to send out recruitment messages to the following WikiProjects on the English Wikipedia, and recruit participants on a voluntary basis:
- WikiProject Women in Red
- Gender Gap Taskforce
- Village Pump
- Tea House
Outside the English Wikipedia:
- Wikimedia research list
The following are example questions. Note that interview questions are not exact, and will be customized for the different contexts.
- What are your perceptions on the gender gaps, specifically content gap in Wikipedia?
- Have you involved in efforts to close the gender gaps?
- What are the challenges you are facing now in terms of the gender gaps?
- What types of improvement would you like to see based on the current efforts?
- What is your perception towards creating AI solutions to close the gender gap?
Step 2: Developing task routing system
Based on our research findings from Step 1, we plan to build systems that address the community issues reflected in them and align our design with the values of the community.
Expected to finish June 30, 2022.
June 2019, IRB modification, identify potential interview participants
July 2019 - present, Step 1: interview community stakeholders
Policy, Ethics and Human Subjects Research
This study was reviewed by the University of Minnesota IRB and approved on February 15, 2019 (see STUDY00005335) and approved with modification on June 28, 2019 (MOD00011592), meeting criteria for exemption from IRB review.
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