Content types influence answers and engagement in supply chain forums
Content associations with answer selection and engagement in supply chain community question answering
Computation and LanguageSocial and Information Networks
Summary
Online question-and-answer platforms help people share knowledge, but it's not always clear what makes a good answer or an engaging question. The authors studied a large collection of logistics-related questions and answers from a Japanese site, looking at the kinds of nouns used. They found that specific logistics terms like “warehouse” are linked to answers chosen as best, while broader terms like “car” or “tax” attract more responses. Their work helps map how different content types relate to community engagement and answer quality in supply chain discussions.
What this means in practice
- •For community managers: Improve question and answer quality control in logistics forums by focusing on content types linked to best-answer selection and engagement patterns.
- •For supply chain analysts: Design better online knowledge-sharing platforms tuned to the language and content that stimulates responses and highlights expert answers in supply chain discussions.
Tested on one dataset.
Authors
Hisatoshi Naganawa
Abstract
Community question-answering platforms are important ecosystems for knowledge sharing, yet research on what makes an answer best or a question engaging has often focused on either individual lexical features or broad topics. This exploratory study examines both levels in Yahoo! Chiebukuro, asking which nouns and semantic noun clusters are associated with best-answer selection and question engagement. We analyze a large corpus of questions and answer-tier posts collected under the keyword logistics, using an offline machine-translation pipeline with manually validated noun-level fidelity. Best-answer selection is modeled with conditional logistic regression within question threads, controlling for answer length, order, and question-answer noun overlap. Engagement is modeled in two stages: whether a question receives any response and, conditional on receiving one, how many responses it attracts. Operational logistics nouns such as distribution, warehouse, and center are associated with best-answer selection, whereas broader civic and infrastructure nouns such as car, tax, and shinkansen are associated with higher engagement. At the cluster level, most semantic noun clusters are associated with best-answer selection, while the clusters associated with response likelihood and response volume are largely distinct. These findings reveal differentiated content-outcome profiles across answer and question levels and provide a domain-wide descriptive map of engagement and answer selection in logistics-related cQA discourse.