2026-10-14T18:21:03Z https://www.scidb.cn/oai

10.57760/sciencedb.29299 2025-08-22T17:27:56Z

2025-08-22 syntax_complexity_data doi:10.57760/sciencedb.29299 en The research data of this study were collected from live-streaming sessions on global e-commerce platforms, including Amazon Live and YouTube Shopping. These broadcasts feature professional English-speaking hosts with established credibility in the e-commerce field, focusing primarily on apparel and home furnishings categories. For analytical purposes, over 400 minutes of live-streaming were captured, subsequently transcribed into textual format, and meticulously verified through manual review.This study built a dependency treebank specifically designed for English e-commerce live-streaming texts (punctuation excluded). A dependency treebank represents a syntactically annotated corpus based on dependency grammar. Within the framework of word grammar—a particular dependency grammar approach—the fundamental unit is the individual word, with sentence structure being entirely composed of categorized relationships between these words (Hudson, 2010). These asymmetric syntactic connections, known as dependency relations, link a governing word, the head, with its dependent. The treebank explicitly marks these heads, dependents, and their dependency relations.The syntactic dependency analysis of the corpora is conducted using Stanford Parser (Version 4.2.0), a tool developed by Stanford University’s Natural Language Processing research team. This software, available for download at https://nlp.stanford.edu/software/lex-parser.shtml#Download, has demonstrated superior annotation accuracy compared to similar tools.  Amazon Live and YouTube Shopping; English-speaking hosts; Stanford Parser ; treebank Lin Wang RESTRICTED dataset http://www.doi.org/10.1515/flin-2025-0130 Science Data Bank