Bibliometric Analysis Description

Our team ran a bibliometric analysis on the literature used in the research proposal using the software VOSViewer. We conducted a text co-occurrence analysis, which looks at how frequently words in titles and abstracts are used. A binary counting method was used; this means that the analysis only considered if words were present or absent in the title/abstract, and does not factor in the number of times that a certain word is used within a document. There was a minimum threshold of five occurrences for a keyword to be included in the analysis. 

network diagram of proposal literature

 

This diagram generated four clusters of terms. A breakdown of the terms found in each cluster can be found below. Overall trends that were realized from this analysis is that newer articles focus on RPA topics while older articles focused more on terms connected to clerical workers.

green square

Green Cluster

- Action
- Application
- Artificial Intelligence
- Company
- Cost
- Field
- Human
- Month
- Nature
- Person
- Practice
- Robotic Process Automation
- RPA

yellow square

Yellow Cluster

- Effect
- Impact
- Office Automation
- Perception
- Performance
- Training

blue square

Blue Cluster

- Change
- Extent
- Productivity
- Relationship
- Skill
- Type
- Way

red square

Red Cluster

- Age
- Analysis
- Articulation Work
- Clerical Work
- Clerical Worker
- Context
- Control
- Cooperative Work
- Evidence
- Gender
- Group
- Job
- Office
- Team
- Woman
- Worker
- Year

NSF logo

logo for National Science Foundation

 

This project is supported by the National Science Foundation (NSF) award #2128495