השוואת שיטות

	זיהוי חזיתות מחקר	VOSviewer ו-CiteSpace: כלים לניתוח ביבליומטרי והדמיה
תחום	ביבליומטריה	ביבליומטריה
משפחה	Process / pipeline	Process / pipeline
שנת המקור	1990s–2000s	2006–2010
הוגה השיטה	Chaomei Chen and others	Nees Jan van Eck & Ludo Waltman (VOSviewer); Chaomei Chen (CiteSpace)
סוג	Method	Tool
מקור מכונן	Chen, C., & Paul, R. J. (1997). Visualizing a knowledge domain's intellectual structure. IEEE Computer, 30(3), 65–71.	Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538.
כינויים	emerging research detection, research frontier mapping, hot topic identification, emerging field analysis	bibliometric mapping software, citation visualization tools, science mapping tools
קשורות	5	4
תקציר	Research front identification is a bibliometric method for detecting emerging or cutting-edge research areas within a larger research landscape. A 'research front' is a cluster of recently published, highly-cited papers that define the current active research direction in a field. Unlike established research communities (identifiable through co-citation networks and slow-changing patterns), research fronts are characterized by rapid growth, high citation velocity (papers accumulating citations quickly), and weak historical ties to established literature. Developed systematically by Chen and others in the 1990s–2000s, research front identification enables researchers, funders, and policy makers to track where scientific activity is concentrating and where breakthrough research is emerging.	VOSviewer and CiteSpace are specialized software tools designed to conduct bibliometric analysis and create science maps from research literature. VOSviewer (developed by Van Eck & Waltman, 2010) excels at creating publication landscapes through co-occurrence, co-citation, and bibliographic coupling analysis with intuitive visual output. CiteSpace (developed by Chaomei Chen, 2006) focuses on detecting emerging research trends and research fronts through direct citation analysis and specialized temporal algorithms. Together, these tools democratized science mapping, enabling researchers without programming expertise to visualize research domains comprehensively.