{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T18:15:47Z","timestamp":1754158547607,"version":"3.41.2"},"reference-count":36,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2018,4,3]],"date-time":"2018-04-03T00:00:00Z","timestamp":1522713600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["EL"],"published-print":{"date-parts":[[2018,4,3]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>In academic work, it is important to identify a specific domain of research. Many researchers may look to conference issues to determine interesting or new topics. Furthermore, conference issues can help researchers identify current research trends in their field and learn about cutting-edge developments in their area of specialization. However, so much conference information is published online that it can be difficult to navigate and analyze in a meaningful or productive way. Hence, the use of knowledge management (KM) could be a way to resolve these issues. In KM, ontology is widely adopted, but most ontology construction methods do not consider social information between target users. Therefore, this study aims to propose a novel method of constructing research topic maps using an open directory project (ODP) and social information.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>The approach is to incorporate conference information (i.e. title, keywords and abstract) as sources and to consider the ways in which social information automatically produces research topic maps. The methodology can be divided into four modules: data collection, element extraction, social information analysis and visualization. The data collection module collects the required conference data from the internet and performs pre-processing. Then, the element extraction module extracts topics, associations and other basic elements of topic maps while considering social information. Finally, the results will be shown in the visualization module for researchers to browse and search.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The results of this study propose three main findings. First, creating topic maps with the ODP category information can help capture a richer set of classification associations. Second, social information should be considered when constructing topic maps. This study includes the relationship among different authors and topics to support information in social networks. By considering social information, such as co-authorship\/collaborator, this method helps researchers find research topics that are unfamiliar but interesting or potential cooperative opportunities in the future. Third, this study presents topic maps that show a clear and simple pathway in interested domain knowledge.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Research limitations implications<\/jats:title>\n<jats:p>First, this study analyzes and collects conference information, including the titles, keywords and abstracts of conference papers, so the data set must include all of the abovementioned information. Second, social information only analyzes co-authorship associations (collabship associations); other social information could be extracted in the future study. Third, this study only analyzes the associations between topics. The intensity of associations is not discussed in the study.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>The study will have a great impact on learned societies because it bridges the gap between theory and practice. The study is useful for researchers who want to know which conferences are related to their research. Moreover, social networks can help researchers expand and diversify their research.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/el-10-2016-0230","type":"journal-article","created":{"date-parts":[[2018,1,29]],"date-time":"2018-01-29T19:26:17Z","timestamp":1517253977000},"page":"220-236","source":"Crossref","is-referenced-by-count":2,"title":["Considering social information in constructing research topic maps"],"prefix":"10.1108","volume":"36","author":[{"given":"Hei Chia","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu Hung","family":"Chiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yen Tzu","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"issue":"5","key":"key2020092917125917200_ref001","doi-asserted-by":"crossref","first-page":"957","DOI":"10.1111\/j.1467-6486.2006.00625.x","article-title":"Co-authorship in management and organizational studies: an empirical and network analysis","volume":"43","year":"2006","journal-title":"Journal of Management Studies"},{"issue":"3","key":"key2020092917125917200_ref002","doi-asserted-by":"crossref","first-page":"6","DOI":"10.5120\/1661-2236","article-title":"Semantic relationship extraction and ontology building using wikipedia: a comprehensive survey","volume":"12","year":"2010","journal-title":"International Journal of Computer Applications"},{"issue":"13","key":"key2020092917125917200_ref003","first-page":"30","article-title":"Comparison of algorithms for social networks using ontology","volume":"85","year":"2014","journal-title":"International Journal of Computer Applications"},{"first-page":"166","article-title":"A survey of ontology evaluation techniques","year":"2005","key":"key2020092917125917200_ref004"},{"key":"key2020092917125917200_ref005","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1016\/j.knosys.2014.03.008","article-title":"Topic knowledge map and knowledge structure constructions with genetic algorithm, information retrieval, and multi-dimension scaling method","volume":"67","year":"2014","journal-title":"Knowledge-Based Systems"},{"issue":"1","key":"key2020092917125917200_ref006","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1007\/s11192-015-1790-4","article-title":"The stability of co-authorship structures","volume":"106","year":"2016","journal-title":"Scientometrics"},{"issue":"4","key":"key2020092917125917200_ref007","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1016\/j.dss.2009.02.011","article-title":"Managing knowledge on the web: extracting ontology from HTML web","volume":"47","year":"2009","journal-title":"Decision Support Systems"},{"issue":"3","key":"key2020092917125917200_ref008","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1016\/j.joi.2011.01.011","article-title":"Articles vs. proceedings papers: do they differ in research relevance and impact? A case study in the library and information science field","volume":"5","year":"2011","journal-title":"Journal of Informetrics"},{"key":"key2020092917125917200_ref009","unstructured":"Hamasaki, M., Matsuo, Y. and Takeda, H. (2007), \u201cOntology extraction using social network\u201d, paper presented at International Workshop on Semantic Web for Collaborative Knowledge Acquisition in Hyderabad."},{"issue":"2","key":"key2020092917125917200_ref010","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1016\/j.ijhm.2007.01.002","article-title":"Visual representation of knowledge networks: a social network analysis of hospitality research domain","volume":"27","year":"2008","journal-title":"International Journal of Hospitality Management"},{"issue":"3","key":"key2020092917125917200_ref011","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1257\/jep.10.3.153","article-title":"Trends in multi-authored papers in economics","volume":"10","year":"1996","journal-title":"The Journal of Economic Perspectives"},{"issue":"4","key":"key2020092917125917200_ref012","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/j.elerap.2010.01.001","article-title":"Coauthorship networks and academic literature recommendation","volume":"9","year":"2010","journal-title":"Electronic Commerce Research and Applications"},{"issue":"6","key":"key2020092917125917200_ref014","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1007\/s11390-005-0855-x","article-title":"Visual ontology construction for digitized art image retrieval","volume":"20","year":"2005","journal-title":"Journal of Computer Science and Technology"},{"issue":"16","key":"key2020092917125917200_ref013","doi-asserted-by":"crossref","first-page":"2794","DOI":"10.1016\/j.ins.2009.04.005","article-title":"Learning and inferencing in user ontology for personalized semantic web search","volume":"179","year":"2009","journal-title":"Information Sciences"},{"issue":"4","key":"key2020092917125917200_ref015","doi-asserted-by":"crossref","first-page":"930","DOI":"10.1016\/j.ipm.2006.08.012","article-title":"Schema and constraints-based matching and merging of topic maps","volume":"43","year":"2007","journal-title":"Information Processing & Management"},{"issue":"3","key":"key2020092917125917200_ref016","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1016\/j.datak.2006.04.001","article-title":"Automated ontology construction for unstructured text documents","volume":"60","year":"2007","journal-title":"Data & Knowledge Engineering"},{"issue":"6","key":"key2020092917125917200_ref017","doi-asserted-by":"crossref","first-page":"1462","DOI":"10.1016\/j.ipm.2005.03.012","article-title":"Co-authorship networks in the digital library research community","volume":"41","year":"2005","journal-title":"Information Processing & Management"},{"issue":"10","key":"key2020092917125917200_ref018","doi-asserted-by":"crossref","first-page":"1173","DOI":"10.1016\/j.technovation.2004.03.001","article-title":"Managing knowledge through collaboration: multiple case studies of managing research in university laboratories in Thailand","volume":"25","year":"2005","journal-title":"Technovation"},{"issue":"4","key":"key2020092917125917200_ref019","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.datak.2011.01.002","article-title":"SyMSS: a syntax-based measure for short-text semantic similarity","volume":"70","year":"2011","journal-title":"Data & Knowledge Engineering"},{"volume-title":"Work at the Boundaries of Science: Information and the Interdisciplinary Research Process","year":"2013","key":"key2020092917125917200_ref020"},{"article-title":"Topic maps","volume-title":"Encyclopedia of Library and Information Sciences","year":"2010","key":"key2020092917125917200_ref021"},{"issue":"9\/10","key":"key2020092917125917200_ref022","first-page":"1737","article-title":"Taxonomy induction based on a collaboratively built knowledge repository","volume":"175","year":"2011","journal-title":"Artificial Intelligence"},{"issue":"3","key":"key2020092917125917200_ref023","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1016\/j.datak.2007.10.001","article-title":"Learning non-taxonomic relationships from web documents for domain ontology construction","volume":"64","year":"2008","journal-title":"Data & Knowledge Engineering"},{"issue":"3","key":"key2020092917125917200_ref024","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1016\/j.knosys.2010.11.003","article-title":"Ontology extraction from relational database: Concept hierarchy as background knowledge","volume":"24","year":"2011","journal-title":"Knowledge-Based Systems"},{"issue":"1","key":"key2020092917125917200_ref025","first-page":"20","article-title":"Information extraction from full text scientific articles: where are the keywords?","volume":"4","year":"2003","journal-title":"BCM Bioinformatics"},{"issue":"3","key":"key2020092917125917200_ref026","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1057\/palgrave.dam.3650074","article-title":"Building a keyword library for description of visual assets: thesaurus basics","volume":"3","year":"2007","journal-title":"Journal of Digital Asset Management"},{"issue":"6","key":"key2020092917125917200_ref027","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1016\/j.acalib.2009.08.006","article-title":"Identifying subject-specific conferences as professional development opportunities for the academic librarian","volume":"35","year":"2009","journal-title":"The Journal of Academic Librarianship"},{"issue":"3","key":"key2020092917125917200_ref028","first-page":"429","article-title":"Topic maps: adopting user-centred indexing technologies in course management systems","volume":"18","year":"2007","journal-title":"Journal of Interactive Learning Research"},{"issue":"2","key":"key2020092917125917200_ref029","doi-asserted-by":"crossref","first-page":"103","DOI":"10.17485\/ijst\/2015\/v8i2\/57771","article-title":"Social information retrieval based on semantic annotation and hashing upon the multiple ontologies","volume":"8","year":"2015","journal-title":"Indian Journal of Science and Technology"},{"key":"key2020092917125917200_ref030","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1007\/978-3-540-92673-3_13","article-title":"Ontology evaluation","volume-title":"Handbook on Ontologies","year":"2009"},{"first-page":"644","article-title":"Journal article topic detection based on semantic features","year":"2009","key":"key2020092917125917200_ref031"},{"issue":"6","key":"key2020092917125917200_ref032","doi-asserted-by":"crossref","first-page":"386","DOI":"10.5771\/0943-7444-2015-6-386","article-title":"Evaluations of a large topic map as a knowledge organization tool for supporting self-regulated learning","volume":"42","year":"2015","journal-title":"Knowledge Organization"},{"issue":"3","key":"key2020092917125917200_ref033","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1108\/EL-11-2014-0197","article-title":"Research on feature-based opinion mining using topic maps","volume":"34","year":"2016","journal-title":"The Electronic Library"},{"issue":"11","key":"key2020092917125917200_ref034","doi-asserted-by":"crossref","first-page":"3252","DOI":"10.1080\/00207543.2012.756152","article-title":"Multi-perspective modeling: managing heterogeneous manufacturing knowledge based on ontologies and topic maps","volume":"51","year":"2013","journal-title":"International Journal of Production Research"},{"issue":"12","key":"key2020092917125917200_ref035","doi-asserted-by":"crossref","first-page":"1898","DOI":"10.1002\/asi.20899","article-title":"Information organization and retrieval using a topic maps-based ontology: results of a task-based evaluation","volume":"59","year":"2008","journal-title":"Journal of the American Society for Information Science and Technology"},{"volume-title":"Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining","year":"2016","key":"key2020092917125917200_ref036"}],"container-title":["The Electronic Library"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/EL-10-2016-0230\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/EL-10-2016-0230\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,25]],"date-time":"2025-07-25T01:08:12Z","timestamp":1753405692000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/el\/article\/36\/2\/220-236\/42985"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,4,3]]},"references-count":36,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2018,4,3]]}},"alternative-id":["10.1108\/EL-10-2016-0230"],"URL":"https:\/\/doi.org\/10.1108\/el-10-2016-0230","relation":{},"ISSN":["0264-0473"],"issn-type":[{"type":"print","value":"0264-0473"}],"subject":[],"published":{"date-parts":[[2018,4,3]]}}}