Extended Abstract: Technical Communication, Correlation And Causation, And The Explication Of Big Data
Keywords
big data; cause and effect; correlations; technical communication
Abstract
Advancements in computational technologies and increased access to large bodies of data have allowed for many pronouncements on the value of big data, especially in the popular press. Examining the culture of big data shows that the past convention where investigators demonstrate the cause and effect rationales in a study has given way to the idea that mere correlations between findings, however unlikely, have value, thus keeping us from more thoughtful and accurate conclusions when examining datasets. Because of this, technical communicators need to take up the challenge of interpretation as they are uniquely situated to better explicate these correlations found in many of today's studies and articles on big data.
Publication Date
9-28-2018
Publication Title
IEEE International Professional Communication Conference
Volume
2018-July
Number of Pages
134-135
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ProComm.2018.00035
Copyright Status
Unknown
Socpus ID
85055771485 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85055771485
STARS Citation
Applen, J. D., "Extended Abstract: Technical Communication, Correlation And Causation, And The Explication Of Big Data" (2018). Scopus Export 2015-2019. 8914.
https://stars.library.ucf.edu/scopus2015/8914