Why We Read Wikipedia (1702.05379v2)

Abstract: Wikipedia is one of the most popular sites on the Web, with millions of users relying on it to satisfy a broad range of information needs every day. Although it is crucial to understand what exactly these needs are in order to be able to meet them, little is currently known about why users visit Wikipedia. The goal of this paper is to fill this gap by combining a survey of Wikipedia readers with a log-based analysis of user activity. Based on an initial series of user surveys, we build a taxonomy of Wikipedia use cases along several dimensions, capturing users' motivations to visit Wikipedia, the depth of knowledge they are seeking, and their knowledge of the topic of interest prior to visiting Wikipedia. Then, we quantify the prevalence of these use cases via a large-scale user survey conducted on live Wikipedia with almost 30,000 responses. Our analyses highlight the variety of factors driving users to Wikipedia, such as current events, media coverage of a topic, personal curiosity, work or school assignments, or boredom. Finally, we match survey responses to the respondents' digital traces in Wikipedia's server logs, enabling the discovery of behavioral patterns associated with specific use cases. For instance, we observe long and fast-paced page sequences across topics for users who are bored or exploring randomly, whereas those using Wikipedia for work or school spend more time on individual articles focused on topics such as science. Our findings advance our understanding of reader motivations and behavior on Wikipedia and can have implications for developers aiming to improve Wikipedia's user experience, editors striving to cater to their readers' needs, third-party services (such as search engines) providing access to Wikipedia content, and researchers aiming to build tools such as recommendation engines.

• The paper develops a taxonomy of reader motivations by correlating survey results with web log data from over 30,000 responses.
• It identifies distinct behavioral patterns for work/school tasks, intrinsic learning, and media-driven reading to highlight targeted user engagement.
• The study suggests actionable improvements for content personalization on Wikipedia through predictive models of user intent.

Understanding Reader Motivations on Wikipedia: A Comprehensive Study

Introduction

Wikipedia serves as one of the most frequented knowledge resources in the digital world, accumulating over 500 million page views daily. Despite being a critical information hub, there has been a limited understanding of why users visit Wikipedia and how they utilize its content. The paper "Why We Read Wikipedia" aims to fill this knowledge gap by systematically analyzing Wikipedia reader behavior and motivations through a combination of survey data and log analysis.

Study Objectives and Methodology

The primary objective of the paper is to build a detailed taxonomy of Wikipedia reader motivations and to quantify these motivations through a large-scale survey, ultimately correlating them with behavior patterns. The authors distributed a well-structured online survey to gather data on user motivations, the depth of information sought, and prior knowledge about the topic being read. This survey resulted in approximately 30,000 responses. In parallel, the paper employed web request logs to track the reading behavior of these participants, uncovering patterns associated with different motivations.

Taxonomy of Reader Motivations

The creation of a taxonomy was a critical component of the research. It categorizes Wikipedia use into three dimensions:

1. Motivation: Includes work/school projects, intrinsic learning, media influence, boredom/random exploration, among others.
2. Information Need: Ranges from quick fact-checks and general overviews to in-depth information searches.
3. Prior Knowledge: Captures whether users were familiar with the topic before visiting Wikipedia.

Survey Analysis and Findings

The survey offered insights into the prevalence of various motivations among Wikipedia users. The findings suggested no overwhelmingly dominant motivation, highlighting a spectrum of reasons such as curiosity, external triggers like media and conversations, or academic/work-related needs. It was evident that Wikipedia is predominantly utilized for brief information needs.

Temporal analysis revealed that motivations remain consistent over time, though work/school motivations and media-influenced visits show distinct patterns correlating with weekdays and weekends, respectively.

Behavioral Patterns from Log Analysis

Using web request logs linked to survey responses, the paper identifies characteristic behaviors associated with different use motivations:

• Work/School: Users often accessed centralized and academic articles via desktop computers, suggesting a focused and directed approach.
• Intrinsic Learning and Boredom: User sessions were longer, with broader topical jumps for bored users, indicating exploration across diverse Wikipedia articles.
• Media-Inspired Reading: Sessions were shorter, with visits to articles more peripheral in the network, often driven by trending topics.
• Current Events and Personal Decisions: These motivations were linked to peaks in visits to articles related to contemporary issues and practical decisions.

Implications and Future Work

The paper’s insights have significant implications for enhancing Wikipedia's user experience. By predicting motivations and tailoring the content delivery accordingly, Wikipedia could better serve distinct user needs, such as providing concise versions of articles for quick fact-checking on mobile devices while offering comprehensive educational resources for deep learning. Future research could focus on improving predictive models that capture the fluid nature of user intentions and extend this research across different language versions to account for cultural diversity in Wikipedia usage.

Conclusion

The paper provides a robust understanding of why people read Wikipedia, revealing a diverse range of use cases and motivations. By bridging survey data with digital behavioral traces, it offers a foundation for developing tools and strategies that can enhance content personalization and Wikipedia’s overall usability. The paper marks a significant step in leveraging user motivation insights to drive the development of intelligent support systems for Wikipedia’s global user base.