Are longer reviews always more helpful? : disentangling the interplay between review length and line of argumentation
| Year of publication: |
2022
|
|---|---|
| Authors: | Lutz, Bernhard ; Pröllochs, Nicolas ; Neumann, Dirk |
| Published in: |
Journal of business research : JBR. - New York, NY : Elsevier, ISSN 0148-2963, ZDB-ID 189773-1. - Vol. 144.2022, p. 888-901
|
| Subject: | Argumentation patterns | Consumer reviews | Data-driven decision-making | Machine learning | Natural language processing | Online word-of-mouth | Künstliche Intelligenz | Artificial intelligence | Virales Marketing | Viral marketing | Konsumentenverhalten | Consumer behaviour | Social Web | Social web |
-
Identifying customer needs from user-generated content
Timoshenko, Artem, (2019)
-
How to strategically respond to online hotel reviews : a strategy-aware deep learning approach
Ku, Chih-Hao, (2024)
-
Exploring the multi-dimensionality of authenticity in dining experiences using online reviews
Le, Truc H., (2021)
- More ...
-
Brammer, Janis, (2022)
-
Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning
Brammer, Janis, (2022)
-
Mörstedt, Torsten, (2024)
- More ...