MANTRA: A Topic Modeling-Based Tool to Support Automated Trend Analysis on Unstructured Social Media Data

DOI to cite this document:: 10.5283/epub.55025

Wörner, Janik ; Konadl, Daniel

; Leist, Susanne

; Schmid, Isabel

PDF
(1MB) - Repository staff only

Date of publication of this fulltext: 20 Nov 2023 09:37

Details

Item type:	Conference or workshop item (Paper)
Date:	10 December 2023
Institutions:	Business, Economics and Information Systems > Institut für Wirtschaftsinformatik > Lehrstuhl für Wirtschaftsinformatik III - Business Engineering (Prof. Dr. Susanne Leist) Informatics and Data Science > Department Information Systems > Lehrstuhl für Wirtschaftsinformatik III - Business Engineering (Prof. Dr. Susanne Leist) Informatics and Data Science
Keywords:	Social Media Analytics, Trend Analysis, Topic Modeling-Based Tool, Design Science, Marketing
Dewey Decimal Classification:	000 Computer science, information & general works > 004 Computer science
Status:	Published
Refereed:	Yes, this version has been refereed
Created at the University of Regensburg:	Yes
Item ID:	55025

Export bibliographical data

Abstract

The early identification of new and auspicious ideas leads to competitive advantages for companies. Thereby, topic modeling can serve as an effective analytical approach for the automated investigation of trends from unstructured social media data. However, existing trend analysis tools do not meet the requirements regarding (a) Product Development, (b) Customer Behavior Analysis, and (c) ...

Owner only: item control page

Download Statistics

More literature (via CORE)

Details

Export bibliographical data

Abstract

Abstract

Download Statistics

Downloads

More literature (via CORE)

University Library