Analyzing total rewards perceptions of marketing professionals through linkedin discourse: a natural language processing approach
Sezai Tunca, Yavuz Selim Balcioglu, Ceren Cubukcu Cerasi, Ayse Bilgen, Ayse Ilgun-Kamanli · 2026
Read Analyzing total rewards perceptions of marketing professionals through linkedin discourse: a natural language processing approach by Sezai Tunca, Yavuz Selim Balcioglu, Ceren Cubukcu Cerasi, Ayse Bilgen, Ayse Ilgun-Kamanli (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13333827.txt.
Description
Sezai Tunca and co-authors mine LinkedIn comments to learn how marketing staff view total rewards in a paper from two thousand twenty-six. Total rewards cover pay, benefits, and growth chances. Public posts show the face professionals present to peers, which the authors treat as signaled preferences.
They analyzed over thirty-five thousand comments from two thousand twenty-three with language models built for the task. Talk of digital skill-based pay rose sharply that year. Flexible work drew strongly positive sentiment, above all in tech. Sector and digital focus together predicted sentiment shifts. The authors read the patterns as early support for a skill-based rewards theory and offer the method for large-scale sentiment work.
Catalog record
| CREATOR | Sezai Tunca, Yavuz Selim Balcioglu, Ceren Cubukcu Cerasi, Ayse Bilgen, Ayse Ilgun-Kamanli |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 146 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |