Stylistic variation in email
This study explores how email is partly shaped by writers’ positions within a corporate structure. This stylistic variation is measurable at scale and can be described by messages’ rhetorical organizations and orientations. The modeling was carried out on a subset of the Enron email corpus, which was processed using the dictionary-based tagger DocuScope. The results identify four stylistic variants (Trained/Technical Support, Decision-Making, Everyday Workplace Interaction, and Engaged Planning), each realizing distinctive combinations of features reflective of their communicative functions. In Trained/Technical Support emails, for example, constellations of words and phrases associated with informational production and facilitation are marshaled in fulfilling routine guidance-seeking and guidance-giving tasks. While writers’ positions motivate stylistic tendencies (e.g., members of upper-level management compose a majority of their messages in the Decision-Making style), all writers avail themselves of a variety of styles, depending on audience and purpose, suggesting that learners might benefit from developing adaptable communicative repertoires.
Keywords: professional communication, computational rhetoric, corpus analysis, computer-mediated communication
Article outline
- 1.Introduction
- 2.Methods
- 2.1The email corpus
- 2.2DocuScope
- 2.3Discriminant analysis
- 3.Results
- 3.1Overview of stylistic variation
- 3.2Trained/Technical Support (Style 1)
- 3.3Decision-Making (Style 2)
- 3.4Everyday Workplace Interaction (Style 3)
- 3.5Engaged Planning (Style 4)
- 4.Discussion and conclusion
- Notes
-
References
Published online: 23 December 2021
https://doi.org/10.1075/rs.20023.bro
https://doi.org/10.1075/rs.20023.bro
References
Biber, D.
(1988) Variation across speech and writing. Cambridge: Cambridge University Press. 
Biber, D., & Gray, B.
(2010) Challenging stereotypes about academic writing: Complexity, elaboration, explicitness. Journal of English for Academic Purposes,
9
(1), 2-20.
Brown, D. W., & Aull, L. L.
(2017) Elaborated specificity versus emphatic generality: A corpus-based comparison of higher-and lower-scoring Advanced Placement exams in English. Research in the Teaching of English,
51
(4), 394–417.
Clarke, I. and Grieve, J.
(2017) Dimensions of abusive language on Twitter. In Proceedings of the First Workshop on Abusive Language Online 1–10. Vancouver: ACL.
Clarke, I., & Grieve, J.
(2019) Stylistic variation on the Donald Trump Twitter account: A linguistic analysis of tweets posted between 2009 and 2018. PlOS ONE,
14
(9), e0222062.
Creamer, G., Rowe, R., Hershkop, S., & Stolfo, S. J.
(2009) Segmentation and automated social hierarchy detection through email network analysis, Berlin, Heidelberg.
De Felice, R., & Garretson, G.
(2018) Politeness at work in the Clinton email corpus: A first look at the effects of status and gender. Corpus Pragmatics,
2
(3), 221–242.
DeJeu, E., & Brown, D. W.
in preparation). Comparing disciplinary variation in student writing across national contexts. In D. W. Brown & D. Wetzel Eds. Between invention and audience: DocuScope and the rhetorical approach to corpus analysis Amsterdam John Benjamins Publishing Company. Manuscript in preparation
Egbert, J., & Biber, D.
(2018) Do all roads lead to Rome? Modeling register variation with factor analysis and discriminant analysis. Corpus Linguistics and Linguistic Theory,
14
(2), 233.
Gilbert, E.
(2012) Phrases that signal workplace hierarchy. Paper presented at the Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work.
Gray, B.
(2013) More than discipline: Uncovering multi-dimensional patterns of variation in academic research articles. Corpora,
8
(2), 153–181.
Hardy, J. A., & Römer, U.
(2013) Revealing disciplinary variation in student writing: A multi-dimensional analysis of the Michigan Corpus of Upper-Level Student Papers (MICUSP). Corpora,
8
(2), 183–207.
Jonsson, E.
(2015) Conversational writing: A multidimensional study of synchronous and supersynchronous computer-mediated communication. New York: Peter Lang International Academic Publishers.
Kaufer, D., Geisler, C., Vlachos, P., & Ishizaki, S.
(2006) Mining textual knowledge for writing education and research: The docuscope project. In L. Van Waes, M. Leijten, & C. M. Neuwirth (Eds.), Writing and digital media (pp. 115–130). Oxford: Elsevier.
Kaufer, D. S., Ishizaki, S., Butler, B. S., & Collins, J.
(2004) The power of words: Unveiling the speaker and writer’s hidden craft. Mahwah, N.J.: Lawrence Erlbaum.
Marcellino, W. M.
(2014) Talk like a marine: USMC linguistic acculturation and civil–military argument. Discourse Studies,
16
(3), 385–405.
McLachlan, G. J.
(2004) Discriminant analysis and statistical pattern recognition. Hoboken, N.J.: Wiley & Sons.
Parry-Giles, S. J., & Kaufer, D. S.
(2017) Memories of Lincoln and the splintering of American political thought. University Park, PA: The Pennsylvania State University Press.
Quirk, R., Greenbaum, S., Leech, G., & Svartvik, J.
(1985) A comprehensive grammar of the English language. London: Pearson Longman.
Shetty, J., & Adibi, J.
(2004) The Enron email dataset database schema and brief statistical report. Information sciences institute technical report, University of Southern California,
4
(1), 120–128.
Taguchi, N., Kaufer, D., Gomez-Laich, P., & Zhao, H.
(2017) A corpus linguistics analysis of on-line peer commentary. Pragmatics and language learning,
14
1, 357–170.
Tootalian, J.
(2017) “To corrupt a man in the midst of a verse”: Ben Jonson and the prose of the world. Ben Jonson Journal,
24
(1), 46–72.
Tsur, O., Littman, A., & Rappoport, A.
(2013) Efficient clustering of short messages into general domains. Paper presented at the Seventh International AAAI Conference on Weblogs and Social Media.
Zhao, H., & Kaufer, D.
(2013) DocuScope for genre analysis: Potential for assessing pragmatic functions. Technology in interlanguage pragmatics research and teaching, 235–260.