Date of Award

6-15-2023

Document Type

Thesis

Publisher

Santa Clara : Santa Clara University, 2023.

Department

Computer Science and Engineering

First Advisor

Kai Lukoff

Abstract

Researchers in many fields, from psychology to privacy studies, want to understand the mobile app ecosystem. The process of reviewing mobile apps is called a ’systematic app review’ (SAR). In a systematic app review, researchers analyze app metadata (e.g., the description, user reviews of the app, the app’s permissions list) and/or the experience of the app itself (e.g., the user interface, the content it contains). Unfortunately, this process does not yet have clearly defined best practices and the process of scraping data from app stores is costly, challenging, and time-consuming for researchers, especially ones without a technical background. Researchers lack a well-documented open-source tool that they can use to scrape mobile app stores for app data.

The goal of this project is to develop an open-source tool that non-technical researchers can use to easily scrape the world’s two most popular mobile app stores: Google Play and Apple App Store. This will empower non-technical researchers to easily conduct systematic app reviews by reducing the time it takes to scrape app stores and eliminating the need to find a third-party technical partner. To do this, we will meet and understand the needs of researchers who wish to conduct systematic app reviews but find it costly to do so, and identify (a) what researchers are looking for in an open-source tool and (b) best practices for conducting systematic app reviews. We then plan to develop our own prototype of an open-source tool based on these needs. Our project will provide non-technical researchers with tools and practices to better understand the current app ecosystem and to identify ways to improve it.


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