Structural complexity predicts consensus readability in online discussions
Bibliographic Data
| ID | 16859244 |
|---|---|
| Authors | Rafik Hadfi (0000-0003-2352-1936, Kyoto University, corresponding author), Takayuki Ito (0000-0001-5093-3886, Kyoto University) |
| Year | 2024 |
| Volume | 14 |
| Issue | 1 |
| Publication date | 2024-03-04 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Network Analysis and Mining (JOURNAL) |
| Journal identifiers | ISSN: 1869-5450 • E-ISSN: 1869-5469 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s13278-024-01212-1 |
| OpenAlex | W4392370696 |
| Language | EN |
| References cited | 46 |
The intricate relationship between structure and function spans various disciplines, from biology to management, offering insights into predicting interesting features of complex systems. This interplay is evident in online forums, where the organization of the threads interacts with the message’s meaning. Assessing readability in these discussions is vital for ensuring information comprehension among diverse audiences. This assessment is challenging due to the complexity of natural language compounded by the social and temporal dynamics within social networks. One practical approach involves aggregating multiple readability metrics as a consensus alignment. In this study, we explore whether the structural complexity of online discussions can predict consensus readability without delving into the semantics of the messages. We propose a consensus readability metric derived from well-known readability tests and a complexity metric applied to the tree structures of Reddit discussions. Our findings indicate that this proposed metric effectively predicts consensus readability based on the complexity of discourse structure
Comprehension · Data science · Information retrieval · Readability · Computer Science · Misinformation and Its Impacts · Psychology · Text Readability and Simplification · Topic Modeling · Artificial Intelligence
Discourse Quality Index
Mapping and Measuring Deliberation
Rhetorical Structure Theory
Derivation of New Readability Formulas (Automated Readability Index, Fog Count and Flesch Reading Ease Formula) for Navy Enlisted Personnel
A Mathematical Theory of Communication
Functional Linguistics
Consensus, Polarization, and Alignment in the Economics Profession
Measuring Political Deliberation
Assessing Readability
| Citation velocity | historical |
|---|---|
| Highly cited | No |