Seunghyun Lee , Jiho Lee , Jae-Min Lee , Hong-Woo Chun , Janghyeok Yoon
{"title":"Linking social media data and patents via Wikipedia for social problem-solving R&D","authors":"Seunghyun Lee , Jiho Lee , Jae-Min Lee , Hong-Woo Chun , Janghyeok Yoon","doi":"10.1016/j.cie.2025.111039","DOIUrl":null,"url":null,"abstract":"<div><div>As modern society develops and changes rapidly, social issues occur in various fields and their impact grows and evolves into social problems. Despite the potential for technology to be a solution to social issues, prior studies have focused on social issue detection, but rarely on identifying practical solutions corresponding to the detected social issues. In this study, we propose an approach that relates social media data to patents to identify existing R&D solutions applicable to social issues. The approach involves 1) extracting core keywords of a detected social issue from social media; 2) expanding the core keywords to R&D keywords using Wikipedia as a bridge database between the social issue and patents; 3) identifying R&D solutions utilizing a search query defined with the core keywords and R&D keywords of the social issue; and 4) analyzing detailed technologies of the R&D solutions. This study contributes to the existing literature by proposing a new approach for linking heterogeneous datasets using Wikipedia. Additionally, this study, which identifies R&D solutions to social issues, offers a new direction for social problem-solving R&D as an extension of prior studies on social issues.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"203 ","pages":"Article 111039"},"PeriodicalIF":6.7000,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Industrial Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360835225001858","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
As modern society develops and changes rapidly, social issues occur in various fields and their impact grows and evolves into social problems. Despite the potential for technology to be a solution to social issues, prior studies have focused on social issue detection, but rarely on identifying practical solutions corresponding to the detected social issues. In this study, we propose an approach that relates social media data to patents to identify existing R&D solutions applicable to social issues. The approach involves 1) extracting core keywords of a detected social issue from social media; 2) expanding the core keywords to R&D keywords using Wikipedia as a bridge database between the social issue and patents; 3) identifying R&D solutions utilizing a search query defined with the core keywords and R&D keywords of the social issue; and 4) analyzing detailed technologies of the R&D solutions. This study contributes to the existing literature by proposing a new approach for linking heterogeneous datasets using Wikipedia. Additionally, this study, which identifies R&D solutions to social issues, offers a new direction for social problem-solving R&D as an extension of prior studies on social issues.
期刊介绍:
Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.