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Grants:Programs/Wikimedia Research Fund/Dynamically Tailored Informational Websites for Improved Knowledge Discovery

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statusnot funded
Dynamically Tailored Informational Websites for Improved Knowledge Discovery
start and end datesJune 1st 2022 to May 31st 2023
budget (USD)30,000-39,999 USD
applicant(s)• Pedro Ferreira

Overview

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Username

Applicant's Wikimedia username. If one is not provided, then the applicant's name will be provided for community review.

Pedro Ferreira

Project title

Dynamically Tailored Informational Websites for Improved Knowledge Discovery

Entity Receiving Funds

Provide the name of the individual or organization that would receive the funds.

Carnegie Mellon University

Research proposal

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Description

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Description of the proposed project, including aims and approach. Be sure to clearly state the problem, why it is important, why previous approaches (if any) have been insufficient, and your methods to address it.

Open and free informational platforms will be the cornerstone of the ecosystem of human knowledge in the very near future. Our project aims at improving these platforms by understating how they can offer a tailored user experience for each and every user in each and every visit. We propose to do so by running a series of randomized control trails, to study how best to help guide the way users navigate the web of knowledge, and by using state-of-the-art machine learning tools, which allow us to characterize the heterogeneity in how users search for information and thus tailor, on the platform on the fly.

Informational websites are complex graphs of pages that grow organically with the needs and visits of users. However, the optimal structure of the graph to meet the needs of one user might be different from the one needed by another user. Also, the optimal structure of the graph that meets the needs of one user in one visit may be different from the one that meets the needs of that same user in another visit with a different purpose. The goal of our project is to present a view of Wikimedia to users that molds itself to the needs of each user and each visit, which can be done, for example, by dynamically adding/removing links among pages or by dynamically highlighting certain links that may be more promising for the quest in hands (e.g. with different color or font size).

In one experiment, we plan to highlight links based on observed traffic, so that we can measure how existing navigation patterns can help future searches. We will drop each participant at a page and ask him/her to navigate the site to learn about a particular topic. We ask him/her to write an essay about the topic, which will later be graded by field experts. This way, we can get at knowledge discovery, retention, and application. We will highlight other links in other experiments to make new graph structures more salient. Our goal is to find the optimal structures for online learning. Perhaps, the best structures for learning are different from all types of network structures known to us today across fields (physics, engineering, social sciences)

This dynamic learning environment can be groundbreaking for building collective intelligence. Different members of a team can be simultaneously presented with access to Wikimedia, each with the optimal view for what they need to learn, making it possible for them to more quickly come together to assemble the obtained distributed knowledge.

Budget

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Approximate amount requested in USD.

30,000-39,999

Budget Description

Briefly describe what you expect to spend money on (specific budgets and details are not necessary at this time).

We have 3 major types of expenses in this project: personal, infrastructure hosting, participants in experiments. Personal is covered by faculty salary and PhD student fellowship. We already have the infrastructure up and running. We need help to cover costs with experiments. We are likely to need 4300 participants, at about 9 each (about 1h of work at minimum wage plus amazon mechanical turk fee),plus 100 experts at about 7.5 (about 1/2h of work with fees), which amounts to $39.450.

Impact

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Address the impact and relevance to the Wikimedia projects, including the degree to which the research will address the 2030 Wikimedia Strategic Direction and/or support the work of Wikimedia user groups, affiliates, and developer communities. If your work relates to knowledge gaps, please directly relate it to the knowledge gaps taxonomy.

We believe that indeed Wikimedia will be essential for the ecosystem of free knowledge in the near future and we believe that our project gets at the core of how it can be so by improving the ways in which information can be given to users. Our project aims at tailoring Wikimedia to provide an enriched experience to each and every user in each and every visit. We aim at better understanding the purpose behind each visit and tailor the way in which Wikimedia meets this purpose by helping users navigate the sea of information before them. We believe that our project can have significant impact for how people learn online and thus will provide significant novel insight for remote and online education moving forward.

Dissemination

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Plans for dissemination.

We will publish our work open and freely on the Internet and give other researchers access to our models and code. One of our goals would be to support the generalization of our findings to all types of informational platforms if appropriate. We also plan to hold a conference on open and free platforms for educational purposes, at Carnegie Mellon University, where we would discuss and show case our findings with a pilot version of a informational website that would be tailored to each user/visit

Past Contributions

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Prior contributions to related academic and/or research projects and/or the Wikimedia and free culture communities. If you do not have prior experience, please explain your planned contributions.

Prior related research include:
  • Hong, Y., Hu, Y., & Burtch, G. (2018). Embeddedness, pro-sociality, and social influence: Evidence from online crowdfunding. MIS Quarterly
  • Burtch, G., Ghose, A., & Wattal, S. (2016). Secret admirers: An empirical examination of information hiding and contribution dynamics in online crowdfunding. Information Systems Research, 27(3), 478-496.
  • Burtch, G., He, Q., Hong, Y., & Lee, D. (2021). How Do Peer Awards Motivate Creative Content? Experimental Evidence from Reddit. Management Science.
  • Matos, M., Ferreira, P., Smith, M. and Telang, R. (2016) Culling the Herd: Using Real-World Randomized Experiments to Measure Social Bias with Known Costly Goods. Management Science 62(9):2563-2580.



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Yes