Massmine Desktop App - UX Design

MassMine: Empowering Researchers

1.0 The Challenge

MassMine simplifies the collection and use of data from online sources, including social media networks like Facebook, Twitter, and Reddit. Funded by the National Endowment for the Humanities, it has been used for research purposes in various subject areas, such as Psychology, Business, Journalism, Epidemiology, Communication, and the Humanities. However, the initial version of Massmine was challenging for non-technical researchers who were unfamiliar with using a command line interface. To address this issue, a graphical user interface was needed. As part of a team of two, my role in the project was to design the workflow and data scraping experiences that would enable researchers to scrape data from Reddit with ease.

Role
UI Designer

Tools
Figma

Links
Massmine.org

2.0 The Approach

We adopted a user-centered design approach, which involved understanding the needs and preferences of our target users. We started by conducting user research to identify pain points, challenges, and opportunities for improvement in the data scraping process. We surveyed and interviewed researchers from different fields who had used data scrapping before to collect data from social media platforms to discover their goals and the most important features.

Based on the user research findings, we developed user personas, which represented the characteristics, motivations, and goals of our target users, whiles also using the opportunity to understand what task flow makes sense to the users. We used these personas to guide our design decisions and ensure that we were designing a user interface that met the needs and expectations of our users.

User Personas

Deductions from the research process required that we approach the design stage with three important principles: the platform should be intuitive; it should be forgiving, with built-in error prevention and recovery features; and accessible. These principles guided the design phase which began with sketches as shown below.

3.0 Low fidelity Sketches

We thought about having a simple input box where users can copy and paste the URL from their target Reddit group or subreddit. A quick preview would help users verify that their data is being exported from the intended page to ensure veracity.
We also saw the need to keep the filtering as the second user task to keep the interface clean and minimal in order to reduce cognitive load for the user. Filtering criteria used through the design were based on available post types from the Reddit platform.
User dashboard iterations to display all scrapped data separated by the progress of the collection.

4.0 High fidelity designs

Step 1: Select Platform

The platform selection page presents users with all web and social media pages available for scrapping data to allow users to choose.
Project Name & Key Variables

This interface allows users to name their projects and also, specify a date range, and define conditional keywords needed in each post
Scrapping Status Indicator

Users are provided an additional scrapping preview that displays a portion of the important parameters defined for the data.
Data Dashboard

An additional dashboard is provided so users can resume other tasks while data is collected in the background

5.0 Usability Testing

We conducted virtual usability tests with some potential users using use-case scenarios. We presented two different scenarios for the testers to try out with our prototype: one of which was collecting data from Reddit directly, while the other scenario was collecting data from specific subreddits with comments. The following deductions were drawn from the test usability test sessions.

5.0 Product Mockups & Reflections

The redesign of this web scraping platform was a challenging project, but ultimately my first successful experience designing products from scratch. We were able to create a design that was both efficient and easy to use, which was important for increasing the productivity of our target audience, particularly non-technical researchers who may now be able to use web scrapping and publicly accessible data. However, I learned that it's important to consider the technical limitations of web scraping, and budget limitations when designing such grant-funded platforms. In this case, ensuring that the platform was able to handle large amounts of data and that the output was in a format that could easily be used for analysis within the limited development budgets.