{"title":"Who Leads Trends on Q&A Platforms? Identifying and Analyzing Trend Discoverers","authors":"Yongning Li, Lun Zhang, Ye Wu, Tianlan Wei","doi":"10.1155/2024/2011436","DOIUrl":null,"url":null,"abstract":"<div>\n <p>Q&A platforms are vital sources of information but often face challenges related to their high ratios of passive to active contributors, which can impede knowledge construction and information exchange on the platforms. This study introduced a novel method for identifying trend discoverers, key users who can detect and initiate discussions on emerging question trends, through response order analysis of data from Zhihu and Stack Overflow. This study underscores the significant role of trend discoverers in influencing question popularity. Trend discoverers not only exhibit higher engagement in knowledge-sharing activities but also participate in discussions across a broader range of topics compared to regular users. The insights derived from this research have crucial implications for improving the development and functionality of Q&A platforms.</p>\n </div>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2024 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/2011436","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Complexity","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/2011436","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Q&A platforms are vital sources of information but often face challenges related to their high ratios of passive to active contributors, which can impede knowledge construction and information exchange on the platforms. This study introduced a novel method for identifying trend discoverers, key users who can detect and initiate discussions on emerging question trends, through response order analysis of data from Zhihu and Stack Overflow. This study underscores the significant role of trend discoverers in influencing question popularity. Trend discoverers not only exhibit higher engagement in knowledge-sharing activities but also participate in discussions across a broader range of topics compared to regular users. The insights derived from this research have crucial implications for improving the development and functionality of Q&A platforms.
期刊介绍：
Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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