Using Natural Language Processing Techniques to Tackle the Construct Identity Problem in Information Systems Research

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Standard

Using Natural Language Processing Techniques to Tackle the Construct Identity Problem in Information Systems Research. / Ludwig, Siegfried; Funk, Burkhardt; Mueller, Benjamin.

Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020: Knowing What We Know: Theory, Meta-analysis, and Review. Hrsg. / Tung X. Bui. Honolulu : University of Hawaiʻi at Mānoa, 2020. S. 5675-5684 (Proceedings of the Annual Hawaii International Conference on System Sciences; Band 2020-January).

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Harvard

Ludwig, S, Funk, B & Mueller, B 2020, Using Natural Language Processing Techniques to Tackle the Construct Identity Problem in Information Systems Research. in TX Bui (Hrsg.), Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020: Knowing What We Know: Theory, Meta-analysis, and Review. Proceedings of the Annual Hawaii International Conference on System Sciences, Bd. 2020-January, University of Hawaiʻi at Mānoa, Honolulu, S. 5675-5684, Hawaii International Conference on System Sciences - HICSS 2020, Hawai, Hawaii, USA / Vereinigte Staaten, 07.01.20. <http://hdl.handle.net/10125/64439>

APA

Ludwig, S., Funk, B., & Mueller, B. (2020). Using Natural Language Processing Techniques to Tackle the Construct Identity Problem in Information Systems Research. in T. X. Bui (Hrsg.), Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020: Knowing What We Know: Theory, Meta-analysis, and Review (S. 5675-5684). (Proceedings of the Annual Hawaii International Conference on System Sciences; Band 2020-January). University of Hawaiʻi at Mānoa. http://hdl.handle.net/10125/64439

Vancouver

Ludwig S, Funk B, Mueller B. Using Natural Language Processing Techniques to Tackle the Construct Identity Problem in Information Systems Research. in Bui TX, Hrsg., Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020: Knowing What We Know: Theory, Meta-analysis, and Review. Honolulu: University of Hawaiʻi at Mānoa. 2020. S. 5675-5684. (Proceedings of the Annual Hawaii International Conference on System Sciences).

Bibtex

@inbook{98d0db8071b64a0ea2c1c7026b3c9b82,
title = "Using Natural Language Processing Techniques to Tackle the Construct Identity Problem in Information Systems Research",
abstract = "The growing number of constructs in behavioral research presents a problem to theory integration, since constructs cannot clearly be discriminated from each other. Recently there have been efforts to employ natural language processing techniques to tackle the construct identity problem. This paper compares the performance of the novel word-embedding model GloVe and different document projection methods with a latent semantic analysis (LSA) used in recent literature. The results show that making use of an advantage in document projection that LSA has over GloVe, performance can be improved. Even against this advantage of LSA, GloVe reaches comparable performance, and adjusted word embedding models can make up for this advantage. The proposed approach therefore presents a promising pathway for theory integration in behavioral research.",
keywords = "Informatics, construct identity fallacy, global vectors for word representation (glove), jingle jangle, latent semantic analysis (lsa), word embeddings",
author = "Siegfried Ludwig and Burkhardt Funk and Benjamin Mueller",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE Computer Society. All rights reserved.; Hawaii International Conference on System Sciences - HICSS 2020, HICSS ; Conference date: 07-01-2020 Through 10-01-2020",
year = "2020",
month = jan,
day = "7",
language = "English",
series = "Proceedings of the Annual Hawaii International Conference on System Sciences",
publisher = "University of Hawaiʻi at Mānoa",
pages = "5675--5684",
editor = "Bui, {Tung X.}",
booktitle = "Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020",
address = "United States",
url = "https://scholarspace.manoa.hawaii.edu/handle/10125/63576",

}

RIS

TY - CHAP

T1 - Using Natural Language Processing Techniques to Tackle the Construct Identity Problem in Information Systems Research

AU - Ludwig, Siegfried

AU - Funk, Burkhardt

AU - Mueller, Benjamin

N1 - Conference code: 53

PY - 2020/1/7

Y1 - 2020/1/7

N2 - The growing number of constructs in behavioral research presents a problem to theory integration, since constructs cannot clearly be discriminated from each other. Recently there have been efforts to employ natural language processing techniques to tackle the construct identity problem. This paper compares the performance of the novel word-embedding model GloVe and different document projection methods with a latent semantic analysis (LSA) used in recent literature. The results show that making use of an advantage in document projection that LSA has over GloVe, performance can be improved. Even against this advantage of LSA, GloVe reaches comparable performance, and adjusted word embedding models can make up for this advantage. The proposed approach therefore presents a promising pathway for theory integration in behavioral research.

AB - The growing number of constructs in behavioral research presents a problem to theory integration, since constructs cannot clearly be discriminated from each other. Recently there have been efforts to employ natural language processing techniques to tackle the construct identity problem. This paper compares the performance of the novel word-embedding model GloVe and different document projection methods with a latent semantic analysis (LSA) used in recent literature. The results show that making use of an advantage in document projection that LSA has over GloVe, performance can be improved. Even against this advantage of LSA, GloVe reaches comparable performance, and adjusted word embedding models can make up for this advantage. The proposed approach therefore presents a promising pathway for theory integration in behavioral research.

KW - Informatics

KW - construct identity fallacy

KW - global vectors for word representation (glove)

KW - jingle jangle

KW - latent semantic analysis (lsa)

KW - word embeddings

UR - http://www.scopus.com/inward/record.url?scp=85082300548&partnerID=8YFLogxK

UR - https://hdl.handle.net/10125/64069

UR - https://www.mendeley.com/catalogue/cf195722-124c-37d7-853c-fc8a935dcfdb/

M3 - Article in conference proceedings

T3 - Proceedings of the Annual Hawaii International Conference on System Sciences

SP - 5675

EP - 5684

BT - Proceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020

A2 - Bui, Tung X.

PB - University of Hawaiʻi at Mānoa

CY - Honolulu

T2 - Hawaii International Conference on System Sciences - HICSS 2020

Y2 - 7 January 2020 through 10 January 2020

ER -

Links