# Data science's cultural construction: qualitative ideas for quantitative work

## TL;DR

This paper explores how data science is defined and discussed on Twitter, revealing both common and emerging themes in the field.

## Contribution

The paper introduces a cultural perspective and complementary datasets to analyze the evolving definition of data science.

## Key findings

- Initial findings show common commercial and technical themes in data science discussions.
- Additional results highlight new practical and ethical standards as a unique aspect of data science.
- The study provides a method for interpreting abstract datasets and guiding data scientists' professional positioning.

## Abstract

“Data scientists” quickly became ubiquitous, often infamously so, but they have struggled with the ambiguity of their novel role. This article studies data science's collective definition on Twitter.

The analysis responds to the challenges of studying an emergent case with unclear boundaries and substance through a cultural perspective and complementary datasets ranging from 1,025 to 752,815 tweets. It brings together relations between accounts that tweeted about data science, the hashtags they used, indicating purposes, and the topics they discussed.

The first results reproduce familiar commercial and technical motives. Additional results reveal concerns with new practical and ethical standards as a distinctive motive for constructing data science.

The article provides a sensibility for local meaning in usually abstract datasets and a heuristic for navigating increasingly abundant datasets toward surprising insights. For data scientists, it offers a guide for positioning themselves vis-à-vis others to navigate their professional future.