Summary of Comparison Between the Structures Of Word Co-occurrence and Word Similarity Networks For Ill-formed and Well-formed Texts in Taiwan Mandarin, by Po-hsuan Huang et al.
Comparison between the Structures of Word Co-occurrence and Word Similarity Networks for Ill-formed and Well-formed Texts in Taiwan Mandarin
by Po-Hsuan Huang, Hsuan-Lei Shao
First submitted to arxiv on: 18 Aug 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Word co-occurrence networks have been studied extensively due to their potential applications. Despite their significance, the study of these networks is crucial to fully understand their structure and usage. Previous research has shown that well-formed texts exhibit certain characteristics, such as being small-world, following a two-regime power law distribution, and being disassortative. In contrast, ill-formed texts like microblog posts may display different properties. While both types of networks are small-world and disassortative, ill-formed text networks are scale-free and follow the power law distribution instead. However, it remains unclear whether these characteristics are universal across languages and comparable networks. This study investigates the structure of word co-occurrence networks built from Taiwan Mandarin internet forum posts and compares them with those built from well-formed judicial judgments, seeking to determine the universality of these properties among different languages and between word co-occurrence and word similarity networks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Word co-occurrence networks are special kinds of maps that show how words relate to each other. Researchers want to understand these maps because they can be useful for many things. They’ve found that some types of texts, like books, have certain patterns. But what about messy texts like social media posts? Do the same patterns appear? Right now, we don’t know if these patterns are true for all languages and kinds of networks. |
