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Wörner, Janik ; Konadl, Daniel ; Leist, Susanne ; Schmid, Isabel

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

Wörner, Janik, Konadl, Daniel , Leist, Susanne and Schmid, Isabel (2023) MANTRA: A Topic Modeling-Based Tool to Support Automated Trend Analysis on Unstructured Social Media Data. In: 44. International Conference on Information Systems (ICIS), 10.12.2023 bis 13.12.2023, Hyderabad, Indien.

Date of publication of this fulltext: 20 Nov 2023 09:37
Conference or workshop item
DOI to cite this document: 10.5283/epub.55025


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) ...

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) Market-/Brand-Monitoring as reflected within extant literature. Thus, based on the requirements for each of these common marketing-related use cases, we derived design principles following design science research and instantiated the artifact “MANTRA” (MArketiNg TRend Analysis). We demonstrated MANTRA on a real-world data set (~1.03 million Yelp reviews) and hereby could confirm remarkable trends of vegan and global cuisine. In particular, the importance of meeting all specific requirements of the respective use cases and especially flexibly incorporating several external parameters into the trend analysis is exemplified.


Involved Institutions


Details

Item typeConference or workshop item (Paper)
Date10 December 2023
InstitutionsBusiness, 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)
KeywordsSocial Media Analytics, Trend Analysis, Topic Modeling-Based Tool, Design Science, Marketing
Dewey Decimal Classification000 Computer science, information & general works > 004 Computer science
StatusPublished
RefereedYes, this version has been refereed
Created at the University of RegensburgYes
Item ID55025

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