Conceptualizing the use of the term financial risk by non-academics and academics using twitter messages and ScienceDirect paper abstracts

A text mining technique, based on an Application Programming Interface (API) request—using narrative data from Twitter ™ and ScienceDirect ™ —was used to identify how non-academics and academics conceptualize and evaluate sentiment indicators associated with the term financial risk in their communic...

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Veröffentlicht in:	Social network analysis and mining Jg. 11; H. 1; S. 6
Hauptverfasser:	Kwak, Eun Jin, Grable, John E.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Vienna Springer Vienna 01.12.2021 Springer Nature B.V
Schlagworte:	Abstracts Academic staff Application programming interface Applications of Graph Theory and Complex Networks Computer Science Concept formation Data analysis Data mining Data Mining and Knowledge Discovery Economics Education Emotions Game Theory Humanities Law Library associations Mass murders Medical libraries Methodology of the Social Sciences Negative emotions Original Original Article Perceptions Policy making Researcher subject relations Risk Risk behavior Risk communication Risk taking Scientific papers Social and Behav. Sciences Social networks Statistics for Social Sciences Teachers Verbal communication Sentiment analysis Twitter and ScienceDirect mining Semantic analysis Financial risk
ISSN:	1869-5450, 1869-5469
Online-Zugang:	Volltext
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