# Characterizing Scalability Issues in Spreadsheet Software using Online Forums

arXiv: https://arxiv.org/abs/1801.03829 · HTML: https://mlsanity.com/paper/1801.03829/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Jan 2018.

## Built on by (most cited first, 1 of 1)

- [Spreadsheet-RL: Advancing Large Language Model Agents on Realistic Spreadsheet Tasks via Reinforcement Learning](https://mlsanity.com/paper/2605.22642/) (2026)

## Abstract (arXiv)

In traditional usability studies, researchers talk to users of tools to understand their needs and challenges. Insights gained via such interviews offer context, detail, and background. Due to costs in time and money, we are beginning to see a new form of tool interrogation that prioritizes scale, cost, and breadth by utilizing existing data from online forums. In this case study, we set out to apply this method of using online forum data to a specific issue---challenges that users face with Excel spreadsheets. Spreadsheets are a versatile and powerful processing tool if used properly. However, with versatility and power come errors, from both users and the software, which make using spreadsheets less effective. By scraping posts from the website Reddit, we collected a dataset of questions and complaints about Excel. Specifically, we explored and characterized the issues users were facing with spreadsheet software in general, and in particular, as resulting from a large amount of data in their spreadsheets. We discuss the implications of our findings on the design of next-generation spreadsheet software.