Startseite UR
![]() | Eine Stufe nach oben |
, Leist, Susanne
und 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.
Zugang zum Volltext eingeschränkt.
Konadl, Daniel, Wörner, Janik, Luttner, Lucas und Leist, Susanne
(2023)
ARTIFICIAL INTELLIGENCE IN AUGMENTATIVE AND ALTERNATIVE COMMUNICATION SYSTEMS – A LITERATURE-BASED ASSESSMENT AND IMPLICATIONS OF DIFFERENT CONVERSATION PHASES AND CONTEXTS.
In: European Conference on Information Systems (ECIS), 12.06.2023 bis 16.06.2023, Kristiansand, Norwegen.
Schmid, Isabel
, Wörner, Janik und Leist, Susanne
(2022)
Automated identification of different lead users regarding the innovation process.
Electronic Markets 32, S. 945-970.
Wörner, Janik, Konadl, Daniel, Schmid, Isabel und Leist, Susanne
(2022)
Supporting Product Development by a Trend Analysis Tool applying Aspect-Based Sentiment Detection.
In: International Conference on Design Science Research in Information Systems and Technology (DESRIST), 01.06. - 03.06.2022, University of South Florida.
(Eingereicht)
Wörner, Janik, Konadl, Daniel, Schmid, Isabel und Leist, Susanne
(2021)
COMPARISON OF TOPIC MODELLING TECHNIQUES IN MARKETING - RESULTS FROM AN ANALYSIS OF DISTINCTIVE USE CASES.
In: 29th European Conference on Information Systems (ECIS2021), 14.06.2021 - 16.06.2021, Virtuell.
Konadl, Daniel, Wörner, Janik und Leist, Susanne
(2021)
Identifying Sentiment Influences Provoked by Context Factors – Results from a Data Analytics Procedure Performed on Tweets.
In:
Proceedings of the 54th Hawaii International Conference on System Sciences (HICSS 2021).
University of Hawai'i at Manoa, Honolulu, HI, S. 2511-2520.
ISBN 978-0-9981331-4-0.
Publikationsserver
Publizieren: oa@ur.de
0941 943 -4239 oder -69394
Dissertationen: dissertationen@ur.de
0941 943 -3904
Forschungsdaten: datahub@ur.de
0941 943 -5707