Experimental Package: Exploring Empathy in Software Engineering Articles

This experimental package contains all files and instructions needed to replicate the data collection and analysis process for gathering and analyzing grey literature articles about empathy in software engineering from DEV.to and Medium, as well as a follow-up expert survey used to assess the resulting framework.

Folder Structure

📁 GL_Study/ – Materials related to the grey literature analysis, including scripts, collected data, the codebook, and coded results.

📁 Experts_Survey/ – Materials related to the expert validation of the framework via survey responses and qualitative analysis.

Contents

📁GL_Study/

dev_scraper.py

Description: Python script using Selenium to scrape articles mentioning "empathy" from DEV.to. It extracts article titles and URLs.

Usage:

Install dependencies:

pip install selenium

Download and configure a WebDriver (e.g., ChromeDriver).

Run the script:

python dev_scraper.py

Output: A CSV file containing the titles and URLs of retrieved articles.

codebook.ods / codebook.xls

Description: Defines thematic codes used during analysis, with descriptions and examples.

Usage: Reference to interpret how themes were applied across the dataset.

coded_articles.ods / coded_articles.xls

Description: Results of the coding process, including:

Article URL

Codes applied for each research question

Usage: Used to explore themes and patterns in the GL dataset.

INSTALL.md – Step-by-step installation guide with example output

REQUIREMENTS.md – Hardware/software requirements and environment details

requirements.txt – Python dependency specification

📁Experts_Survey/

Framework.pdf

Description: Visual representation of the empathy framework assessed by experts.

Complete Survey - Framework Assessment.pdf

Description: Full survey instrument used to collect expert feedback on the proposed empathy framework. Includes all questions

and response options.

Raw data responses.xlsx / Raw data responses.ods

Description: Raw qualitative responses submitted by expert participants.

Data analysis survey experts.xlsx /Data analysis survey experts.ods

Description: Thematic analysis and applied coding of the expert responses.

Prerequisites

Python 3.7+ – Required to run dev_scraper.py

Selenium WebDriver – ChromeDriver or another driver, depending on your browser

ImportJSON - Script to enable JSON import functionality in Google Sheets

Google Sheets – For running the IMPORTJSON.gs script

Spreadsheet software – To open .xls or .ods files (e.g., LibreOffice, Excel)

Basic understanding of qualitative coding – To interpret the results using the codebook

Steps to Replicate

Collect Articles from DEV.to

Use dev_scraper.py or the IMPORTJSON.gs script to retrieve articles about empathy.

Using IMPORTJSON.gs

Description: Google Sheets script for pulling articles tagged "empathy" via the DEV.to API.

Usage:1. Download the script2. Add to Google Sheets script editor (instructions).3. Use the formula:

```
=ImportJSON("https://dev.to/api/articles?tag=empathy;per_page=1000")
```

Output: A structured table with metadata for up to 1000 empathy-tagged articles.

Review and Apply the Codebook

Consult codebook.ods or codebook.xls for definitions and examples of each code.

Analyze the Grey Literature Data

Use coded_articles.ods or coded_articles.xls to explore the application of codes.

Review the Expert Survey Data (optional)

Refer to the expert feedback survey and its analysis to understand the validation of the framework.

License

This replication package is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0).

You are free to share, adapt, and build upon this material for any purpose—even commercially—provided that proper credit is given and any derivatives are distributed under the same license.

For more information, see the CC BY-SA 4.0 License.

📄 Citation

If you use this dataset in your research, please cite: Cerqueira, L. (2025). Experimental Package: Exploring Empathy in Software Engineering Articles (1.5) [Data set]. Zenodo. 10.5281/zenodo.15800354

Contact

For questions or additional information, please contact:

Lidiany [e-mail] University of Bahia (UFBA)