---
_id: '35732'
abstract:
- lang: eng
text: While the Information Systems (IS) discipline has researched digital platforms
extensively, the body of knowledge appertaining to platforms still appears fragmented
and lacking conceptual consistency. Based on automated text mining and unsupervised
machine learning, we collect, analyze, and interpret the IS discipline’s comprehensive
research on platforms—comprising 11,049 papers spanning 44 years of research activity.
From a cluster analysis concerning platform concepts’ semantically most similar
words, we identify six research streams on platforms, each with their own platform
terms. Based on interpreting the identified concepts vis-à-vis the extant research
and considering a temporal perspective on the concepts’ application, we present
a lexicon of platform concepts, to guide further research on platforms in the
IS discipline. Researchers and managers can build on our results to position their
work appropriately, applying a specific theoretical perspective on platforms in
isolation or combining multiple perspectives to study platform phenomena at a
more abstract level.
article_type: original
author:
- first_name: Christian
full_name: Bartelheimer, Christian
id: '49160'
last_name: Bartelheimer
- first_name: Philipp
full_name: zur Heiden, Philipp
id: '64394'
last_name: zur Heiden
- first_name: Hedda
full_name: Lüttenberg, Hedda
last_name: Lüttenberg
- first_name: Daniel
full_name: Beverungen, Daniel
id: '59677'
last_name: Beverungen
citation:
ama: 'Bartelheimer C, zur Heiden P, Lüttenberg H, Beverungen D. Systematizing the
lexicon of platforms in information systems: a data-driven study. Electronic
Markets. 2022;32:375-396. doi:10.1007/s12525-022-00530-6'
apa: 'Bartelheimer, C., zur Heiden, P., Lüttenberg, H., & Beverungen, D. (2022).
Systematizing the lexicon of platforms in information systems: a data-driven study.
Electronic Markets, 32, 375–396. https://doi.org/10.1007/s12525-022-00530-6'
bibtex: '@article{Bartelheimer_zur Heiden_Lüttenberg_Beverungen_2022, title={Systematizing
the lexicon of platforms in information systems: a data-driven study}, volume={32},
DOI={10.1007/s12525-022-00530-6},
journal={Electronic Markets}, publisher={Springer Science and Business Media LLC},
author={Bartelheimer, Christian and zur Heiden, Philipp and Lüttenberg, Hedda
and Beverungen, Daniel}, year={2022}, pages={375–396} }'
chicago: 'Bartelheimer, Christian, Philipp zur Heiden, Hedda Lüttenberg, and Daniel
Beverungen. “Systematizing the Lexicon of Platforms in Information Systems: A
Data-Driven Study.” Electronic Markets 32 (2022): 375–96. https://doi.org/10.1007/s12525-022-00530-6.'
ieee: 'C. Bartelheimer, P. zur Heiden, H. Lüttenberg, and D. Beverungen, “Systematizing
the lexicon of platforms in information systems: a data-driven study,” Electronic
Markets, vol. 32, pp. 375–396, 2022, doi: 10.1007/s12525-022-00530-6.'
mla: 'Bartelheimer, Christian, et al. “Systematizing the Lexicon of Platforms in
Information Systems: A Data-Driven Study.” Electronic Markets, vol. 32,
Springer Science and Business Media LLC, 2022, pp. 375–96, doi:10.1007/s12525-022-00530-6.'
short: C. Bartelheimer, P. zur Heiden, H. Lüttenberg, D. Beverungen, Electronic
Markets 32 (2022) 375–396.
date_created: 2023-01-10T10:00:55Z
date_updated: 2024-04-18T12:40:34Z
ddc:
- '380'
department:
- _id: '526'
doi: 10.1007/s12525-022-00530-6
file:
- access_level: closed
content_type: application/pdf
creator: dabe
date_created: 2024-04-18T12:39:00Z
date_updated: 2024-04-18T12:39:00Z
file_id: '53573'
file_name: EM - Lexicon of Platform Terms.pdf
file_size: 1262427
relation: main_file
success: 1
file_date_updated: 2024-04-18T12:39:00Z
has_accepted_license: '1'
intvolume: ' 32'
jel:
- L86
keyword:
- Platform
- Text mining
- Machine learning
- Data communications
- Interpretive research
- Systems design and implementation
language:
- iso: eng
page: 375-396
publication: Electronic Markets
publication_identifier:
issn:
- 1019-6781
- 1422-8890
publication_status: published
publisher: Springer Science and Business Media LLC
quality_controlled: '1'
status: public
title: 'Systematizing the lexicon of platforms in information systems: a data-driven
study'
type: journal_article
user_id: '59677'
volume: 32
year: '2022'
...
---
_id: '1154'
author:
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
citation:
ama: 'Geierhos M. Text Mining. In: Gronau N, Becker J, Sinz E, Suhl L, Leimeister
JM, eds. Enzyklopädie der Wirtschaftsinformatik. 9th ed. Berlin, Germany:
GITO-Verlag; 2016.'
apa: 'Geierhos, M. (2016). Text Mining. In N. Gronau, J. Becker, E. Sinz, L. Suhl,
& J. M. Leimeister (Eds.), Enzyklopädie der Wirtschaftsinformatik (9th
ed.). Berlin, Germany: GITO-Verlag.'
bibtex: '@inbook{Geierhos_2016, place={Berlin, Germany}, edition={9}, title={Text
Mining}, booktitle={Enzyklopädie der Wirtschaftsinformatik}, publisher={GITO-Verlag},
author={Geierhos, Michaela}, editor={Gronau, Norbert and Becker, Jörg and Sinz,
Elmar and Suhl, Leena and Leimeister, Jan M.Editors}, year={2016} }'
chicago: 'Geierhos, Michaela. “Text Mining.” In Enzyklopädie der Wirtschaftsinformatik,
edited by Norbert Gronau, Jörg Becker, Elmar Sinz, Leena Suhl, and Jan M. Leimeister,
9th ed. Berlin, Germany: GITO-Verlag, 2016.'
ieee: 'M. Geierhos, “Text Mining,” in Enzyklopädie der Wirtschaftsinformatik,
9th ed., N. Gronau, J. Becker, E. Sinz, L. Suhl, and J. M. Leimeister, Eds. Berlin,
Germany: GITO-Verlag, 2016.'
mla: Geierhos, Michaela. “Text Mining.” Enzyklopädie der Wirtschaftsinformatik,
edited by Norbert Gronau et al., 9th ed., GITO-Verlag, 2016.
short: 'M. Geierhos, in: N. Gronau, J. Becker, E. Sinz, L. Suhl, J.M. Leimeister
(Eds.), Enzyklopädie der Wirtschaftsinformatik, 9th ed., GITO-Verlag, Berlin,
Germany, 2016.'
date_created: 2018-01-31T14:06:36Z
date_updated: 2022-01-06T06:51:02Z
department:
- _id: '36'
- _id: '1'
- _id: '579'
edition: '9'
editor:
- first_name: Norbert
full_name: Gronau, Norbert
last_name: Gronau
- first_name: Jörg
full_name: Becker, Jörg
last_name: Becker
- first_name: Elmar
full_name: Sinz, Elmar
last_name: Sinz
- first_name: Leena
full_name: Suhl, Leena
last_name: Suhl
- first_name: Jan M.
full_name: Leimeister, Jan M.
last_name: Leimeister
keyword:
- Text Mining
language:
- iso: ger
main_file_link:
- open_access: '1'
url: http://www.wi-lex.de/lexikon/technologien-methoden/text-mining/text-mining/?searchterm=text%20mining
oa: '1'
place: Berlin, Germany
publication: Enzyklopädie der Wirtschaftsinformatik
publication_status: published
publisher: GITO-Verlag
quality_controlled: '1'
status: public
title: Text Mining
type: encyclopedia_article
user_id: '13929'
year: '2016'
...
---
_id: '4690'
author:
- first_name: Elena
full_name: Gorbacheva, Elena
last_name: Gorbacheva
- first_name: Armin
full_name: Stein, Armin
last_name: Stein
- first_name: Theresa
full_name: Schmiedel, Theresa
last_name: Schmiedel
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: Gorbacheva E, Stein A, Schmiedel T, Müller O. The Role of Gender in Business
Process Management Competence Supply. Business and Information Systems Engineering.
2016;(3):213--231. doi:10.1007/s12599-016-0428-2
apa: Gorbacheva, E., Stein, A., Schmiedel, T., & Müller, O. (2016). The Role
of Gender in Business Process Management Competence Supply. Business and Information
Systems Engineering, (3), 213--231. https://doi.org/10.1007/s12599-016-0428-2
bibtex: '@article{Gorbacheva_Stein_Schmiedel_Müller_2016, title={The Role of Gender
in Business Process Management Competence Supply}, DOI={10.1007/s12599-016-0428-2},
number={3}, journal={Business and Information Systems Engineering}, author={Gorbacheva,
Elena and Stein, Armin and Schmiedel, Theresa and Müller, Oliver}, year={2016},
pages={213--231} }'
chicago: 'Gorbacheva, Elena, Armin Stein, Theresa Schmiedel, and Oliver Müller.
“The Role of Gender in Business Process Management Competence Supply.” Business
and Information Systems Engineering, no. 3 (2016): 213--231. https://doi.org/10.1007/s12599-016-0428-2.'
ieee: E. Gorbacheva, A. Stein, T. Schmiedel, and O. Müller, “The Role of Gender
in Business Process Management Competence Supply,” Business and Information
Systems Engineering, no. 3, pp. 213--231, 2016.
mla: Gorbacheva, Elena, et al. “The Role of Gender in Business Process Management
Competence Supply.” Business and Information Systems Engineering, no. 3,
2016, pp. 213--231, doi:10.1007/s12599-016-0428-2.
short: E. Gorbacheva, A. Stein, T. Schmiedel, O. Müller, Business and Information
Systems Engineering (2016) 213--231.
date_created: 2018-10-12T08:29:58Z
date_updated: 2022-01-06T07:01:18Z
doi: 10.1007/s12599-016-0428-2
extern: '1'
issue: '3'
keyword:
- BPM workforce
- Business process management
- Competences
- Gender diversity
- Latent semantic analysis
- Skills
- Text mining
language:
- iso: eng
page: 213--231
publication: Business and Information Systems Engineering
publication_identifier:
issn:
- '18670202'
status: public
title: The Role of Gender in Business Process Management Competence Supply
type: journal_article
user_id: '72849'
year: '2016'
...
---
_id: '4691'
abstract:
- lang: eng
text: Analysts have estimated that more than 80 percent of today’s data is stored
in unstructured form (e.g., text, audio, image, video)—much of it expressed in
rich and ambiguous natural language. Traditionally, to analyze natural language,
one has used qualitative data-analysis approaches, such as manual coding. Yet,
the size of text data sets obtained from the Internet makes manual analysis virtually
impossible. In this tutorial, we discuss the challenges encountered when applying
automated text-mining techniques in information systems research. In particular,
we showcase how to use probabilistic topic modeling via Latent Dirichlet allocation,
an unsupervised text-mining technique, with a LASSO multinomial logistic regression
to explain user satisfaction with an IT artifact by automatically analyzing more
than 12,000 online customer reviews. For fellow information systems researchers,
this tutorial provides guidance for conducting text-mining studies on their own
and for evaluating the quality of others.
author:
- first_name: Stefan
full_name: Debortoli, Stefan
last_name: Debortoli
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Iris
full_name: Junglas, Iris
last_name: Junglas
- first_name: Jan
full_name: vom Brocke, Jan
last_name: vom Brocke
citation:
ama: 'Debortoli S, Müller O, Junglas I, vom Brocke J. Text Mining for Information
Systems Researchers: An Annotated Tutorial. Communications of the Association
for Information Systems. Published online 2016:555-582. doi:10.17705/1CAIS.03907'
apa: 'Debortoli, S., Müller, O., Junglas, I., & vom Brocke, J. (2016). Text
Mining for Information Systems Researchers: An Annotated Tutorial. Communications
of the Association for Information Systems, 555–582. https://doi.org/10.17705/1CAIS.03907'
bibtex: '@article{Debortoli_Müller_Junglas_vom Brocke_2016, title={Text Mining for
Information Systems Researchers: An Annotated Tutorial}, DOI={10.17705/1CAIS.03907},
journal={Communications of the Association for Information Systems}, author={Debortoli,
Stefan and Müller, Oliver and Junglas, Iris and vom Brocke, Jan}, year={2016},
pages={555–582} }'
chicago: 'Debortoli, Stefan, Oliver Müller, Iris Junglas, and Jan vom Brocke. “Text
Mining for Information Systems Researchers: An Annotated Tutorial.” Communications
of the Association for Information Systems, 2016, 555–82. https://doi.org/10.17705/1CAIS.03907.'
ieee: 'S. Debortoli, O. Müller, I. Junglas, and J. vom Brocke, “Text Mining for
Information Systems Researchers: An Annotated Tutorial,” Communications of
the Association for Information Systems, pp. 555–582, 2016, doi: 10.17705/1CAIS.03907.'
mla: 'Debortoli, Stefan, et al. “Text Mining for Information Systems Researchers:
An Annotated Tutorial.” Communications of the Association for Information Systems,
2016, pp. 555–82, doi:10.17705/1CAIS.03907.'
short: S. Debortoli, O. Müller, I. Junglas, J. vom Brocke, Communications of the
Association for Information Systems (2016) 555–582.
date_created: 2018-10-12T08:30:04Z
date_updated: 2026-03-10T09:44:54Z
department:
- _id: '196'
doi: 10.17705/1CAIS.03907
extern: '1'
keyword:
- Latent dirichlet allocation
- Online customer reviews
- Text mining
- Topic modeling
- User satisfaction
language:
- iso: eng
page: 555-582
publication: Communications of the Association for Information Systems
publication_identifier:
isbn:
- '9781615679119'
issn:
- 1529-3181
status: public
title: 'Text Mining for Information Systems Researchers: An Annotated Tutorial'
type: journal_article
user_id: '14972'
year: '2016'
...
---
_id: '4695'
author:
- first_name: Stefan
full_name: Debortoli, Stefan
last_name: Debortoli
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
- first_name: Jan
full_name: vom Brocke, Jan
last_name: vom Brocke
citation:
ama: 'Debortoli S, Müller O, vom Brocke J. Comparing business intelligence and big
data skills: A text mining study using job advertisements. Business and Information
Systems Engineering. 2014;(5):289--300. doi:10.1007/s12599-014-0344-2'
apa: 'Debortoli, S., Müller, O., & vom Brocke, J. (2014). Comparing business
intelligence and big data skills: A text mining study using job advertisements.
Business and Information Systems Engineering, (5), 289--300. https://doi.org/10.1007/s12599-014-0344-2'
bibtex: '@article{Debortoli_Müller_vom Brocke_2014, title={Comparing business intelligence
and big data skills: A text mining study using job advertisements}, DOI={10.1007/s12599-014-0344-2},
number={5}, journal={Business and Information Systems Engineering}, author={Debortoli,
Stefan and Müller, Oliver and vom Brocke, Jan}, year={2014}, pages={289--300}
}'
chicago: 'Debortoli, Stefan, Oliver Müller, and Jan vom Brocke. “Comparing Business
Intelligence and Big Data Skills: A Text Mining Study Using Job Advertisements.”
Business and Information Systems Engineering, no. 5 (2014): 289--300. https://doi.org/10.1007/s12599-014-0344-2.'
ieee: 'S. Debortoli, O. Müller, and J. vom Brocke, “Comparing business intelligence
and big data skills: A text mining study using job advertisements,” Business
and Information Systems Engineering, no. 5, pp. 289--300, 2014.'
mla: 'Debortoli, Stefan, et al. “Comparing Business Intelligence and Big Data Skills:
A Text Mining Study Using Job Advertisements.” Business and Information Systems
Engineering, no. 5, 2014, pp. 289--300, doi:10.1007/s12599-014-0344-2.'
short: S. Debortoli, O. Müller, J. vom Brocke, Business and Information Systems
Engineering (2014) 289--300.
date_created: 2018-10-12T08:30:31Z
date_updated: 2022-01-06T07:01:18Z
doi: 10.1007/s12599-014-0344-2
extern: '1'
issue: '5'
keyword:
- Big data
- Business intelligence
- Competencies
- Latent semantic analysis
- Text mining
language:
- iso: eng
page: 289--300
publication: Business and Information Systems Engineering
publication_identifier:
isbn:
- 0910-8327 (Print)$\backslash$n0910-8327 (Linking)
issn:
- '18670202'
status: public
title: 'Comparing business intelligence and big data skills: A text mining study using
job advertisements'
type: journal_article
user_id: '72849'
year: '2014'
...