discon is a collection of R tools to enhance analysis of discourse connectors in text. Discourse connectors are cohesive devices that can be used to help identify themes within a text. This package provides computational means of extracting and visualizing various elements from the text that contain discourse connectors. This can assist in qualitative analysis of discourse by identifying categories that may aide analysis (using the computer for efficiency and data coverage) towards generating themes.
Discourse connectors are devices used to bridge between turns (in speech) and sentences, indicating the logical relations among the parts of a the logical relations among the parts of a framework for the listener/reader. There are two major classes of discourse connectors: discourse markers and linking adverbials. Discourse markers – forms like ok, well, and now – are restricted primarily to spoken discourse. These forms have distinct discourse functions, but it is difficult to identify the specific meaning of the word itself. In contrast, linking adverbials – forms like however, thus, therefore, for example (e.g.), and that is (i.e.) – are found in both spoken and written registers, and they have greater inherent meaning than discourse markers. (Biber, 2006, p. 66)
Please see the following resources for additional information:
- Alemany, L. A. (2005). Representing discourse for automatic text summarization via shallow NLP techniques (Unpublished doctoral dissertation). Universitat de Barcelona, Barcelona.
- Biber, D. (2006). University language: A corpus-based study of spoken and written registers. Amsterdam: John Benjamins Publishing Company.
- Halliday, M. A. K. & Hasan, R. (1976). Cohesion in English. English Language Series. London: Longman.
- Kalajahi, S. A. R., Abdullah, A. N., Mukundan, J., & Tannacito, D. J. (2012). Discourse connectors: An overview of the history, definition and classification of the term. World Applied Sciences Journal, 19(11), 1659-1673.
- Linguistic Data Consortium. (2004) Simple metadata annotation specification (MDE). University of Pennsylvania. Retrieved from http://www.itl.nist.gov/iad/mig/tests/rt/2004-fall/docs/SimpleMDE_V6.2-draft.pdf
- Ryan, G. W. & Bernard, H. R. (2003). Techniques to identify themes. Field Methods. 15(1), 85-109. doi:10.1177/1525822X02239569.
- Schiffrin, D. (1987). Discourse markers. London: Cambridge University Press.
- Schiffrin, D. (2001). Discourse markers: Language, meaning, and context. In D. Schiffrin, D., D. Tannen, & H. E. Hamilton, (Eds.) The handbook of discourse analysis (pp. 54-75). Malden, MA: Blackwell Publishing.
- Ward, N. (2000, October). Issues in the Transcription of English Conversational Grunts. Proceedings of the 1st SIGdial Workshop on Discourse and Dialogue (pp. 29—35). Hong Kong: Association for Computational Linguistics. Retrieved from http://www.aclweb.org/anthology/W00-1004
To download the development version of discon:
Download the zip ball or tar ball, decompress and run R CMD INSTALL on it, or use the pacman package to install the development version:
if (!require("pacman")) install.packages("pacman")
pacman::p_load_gh(
"trinker/qdapRegex",
"trinker/qdapTools",
"trinker/qdapDictionaries",
"trinker/qdap",
"trinker/discon"
)You are welcome to:
- submit suggestions and bug-reports at: https://github.com/trinker/discon/issues
- send a pull request on: https://github.com/trinker/discon/
- compose a friendly e-mail to: tyler.rinker@gmail.com
discourse_connector&discourse_connector_logicaldc_backchanneldc_causality&dc_causality_subdc_comparisondc_connective&dc_connective_subdc_context&dc_context_subdc_equality&dc_equality_subdc_filled_pausedc_negatordc_oh&dc_oh_begindc_revisiondc_timingdc_typologydc_well&dc_well_beginkwic(Key Words in Context)
*Note that all discourse_connector based functions (incuding functions prefixed with dc_) have generic plot method that utilizes qdap::dispersion_plot to generate a lexical dispersion plot.
Specific discourse connector functions for exploring the context in which such markers are used. Note these functions are prefixed with a dc_ (for discourse connector).
causality_1 <- with(pres_debates2012, dc_causality(dialogue, person))
plot(causality_1)
plot(causality_1[[1]], high = "darkgreen")
causality_1[1]$counts
person word.count causality
1 OBAMA 18317 220(1.20%)
2 ROMNEY 19923 148(.74%)
3 CROWLEY 1670 24(1.44%)
4 LEHRER 765 4(.52%)
5 QUESTION 583 3(.51%)
6 SCHIEFFER 1445 13(.90%)
head(causality_1[[2]])===================================
Event 1: [lines 5-7]
LEHRER: And what about the vouchers?
** ROMNEY: <<So that>>'s that's number one.
ROMNEY: Number two is for people coming along that are young,
what I do to make sure that we can keep Medicare in place
for them is to allow them either to choose the current
Medicare program or a private plan.
===================================
Event 2: [lines 9-11]
ROMNEY: They get to choose and they'll have at least two plans
that will be entirely at no cost to them.
** ROMNEY: <<So>> they don't have to pay additional money, no
additional dollar six thousand.
ROMNEY: That's not going to happen.
causality_2 <- with(pres_debates2012, dc_causality_sub(dialogue, person))
plot(causality_2, bg.color = "grey60", color = "blue",
total.color = "grey40", horiz.color="grey20")
causality_2[1]$counts
person word.count continuation elaboration
1 OBAMA 18317 127(.69%) 93(.51%)
2 ROMNEY 19923 93(.47%) 55(.28%)
3 CROWLEY 1670 11(.66%) 13(.78%)
4 LEHRER 765 4(.52%) 0
5 QUESTION 583 1(.17%) 2(.34%)
6 SCHIEFFER 1445 7(.48%) 6(.42%)
head(causality_2[[2]])===================================
Event 1: [lines 5-7]
LEHRER: And what about the vouchers?
** ROMNEY: <<So that>>'s that's number one.
ROMNEY: Number two is for people coming along that are young,
what I do to make sure that we can keep Medicare in place
for them is to allow them either to choose the current
Medicare program or a private plan.
===================================
Event 2: [lines 9-11]
ROMNEY: They get to choose and they'll have at least two plans
that will be entirely at no cost to them.
** ROMNEY: <<So>> they don't have to pay additional money, no
additional dollar six thousand.
ROMNEY: That's not going to happen.
head(causality_2[[3]])===================================
Event 1: [lines 106-108]
OBAMA: Now, it wasn't just on Wall Street.
** OBAMA: You had loan officers were that were giving loans and
mortgages that really shouldn't have been given,
<<because>> the folks didn't qualify.
OBAMA: You had people who were borrowing money to buy a house
that they couldn't afford.
===================================
Event 2: [lines 120-122]
OBAMA: And so the question is: Does anybody out there think that
the big problem we had is that there was too much
oversight and regulation of Wall Street?
** OBAMA: <<Because>> if you do, then Governor Romney is your
candidate.
OBAMA: But that's not what I believe.
revision <- with(pres_debates2012[1:20, ], dc_revision(dialogue, person))
revision[1]$counts
person word.count revision
1 ROMNEY 260 2(.77%)
2 LEHRER 24 1(4.17%)
revision[2]$revision
===================================
Event 1: [lines 1-3]
LEHRER: We'll talk about specifically about health care in a
moment.
** LEHRER: <<But>> what do you support the voucher system, Governor?
ROMNEY: What I support is no change for current retirees and near
retirees to Medicare.
===================================
Event 2: [lines 17-19]
ROMNEY: If I don't like them, I can get rid of them and find a
different insurance company.
** ROMNEY: <<But>> people make their own choice.
ROMNEY: The other thing we have to do to save Medicare?
===================================
Event 3: [lines 19-20]
ROMNEY: The other thing we have to do to save Medicare?
** ROMNEY: We have to have the benefits high for those that are low
income, <<but>> for higher income people, we're going to
have to lower some of the benefits.
typology <- with(pres_debates2012[1:120, ], dc_typology(dialogue, person))
typology[1]$counts
person word.count positive negative
1 OBAMA 510 1(.20%) 0
2 ROMNEY 718 3(.42%) 0
3 LEHRER 203 1(.49%) 1(.49%)
typology[2]$positive
===================================
Event 1: [lines 41-43]
OBAMA: And so|
** ROMNEY: That's <<that's a>> big topic.
ROMNEY: Can we can we stay on Medicare?
===================================
Event 2: [lines 98-100]
ROMNEY: You need transparency, you need to have leverage limits
for|
** LEHRER: Well, <<here's a>> specific|
ROMNEY: But let's let's mention let me mention the other one.
===================================
Event 3: [lines 103-105]
LEHRER: Let's let him respond let's let him respond to this
specific on Dodd Frank and what the governor just said.
** OBAMA: I think this <<is a>> great example.
OBAMA: The reason we have been in such a enormous economic
crisis was prompted by reckless behavior across the
board.
typology[3]$negative
===================================
Event 1: [lines 66-68]
LEHRER: Beginning with you.
** LEHRER: This <<is not a>> new two minute segment to start.
LEHRER: And we'll go for a few minutes, and then we're going to
go to health care, OK?
We will now examine discourse_connector, the basic root function that all of the other dc_ prefixed functions are based upon. This can be used by the researcher to find specific text elements + surrounding context.
## Marker with one type (just: "I")
i_disc <- with(pres_debates2012, discourse_connector(dialogue, person,
names = c("I"),
regex = "\\bI('[a-z]+)*\\b",
terms = list(I = c(" I ", " I'"))
))
i_disc[[1]] person word.count I
1 OBAMA 18317 330(1.80%)
2 ROMNEY 19923 505(2.53%)
3 CROWLEY 1670 49(2.93%)
4 LEHRER 765 9(1.18%)
5 QUESTION 583 18(3.09%)
6 SCHIEFFER 1445 25(1.73%)
head(i_disc[[2]])===================================
Event 1: [lines 2-4]
LEHRER: But what do you support the voucher system, Governor?
** ROMNEY: What <<I>> support is no change for current retirees and
near retirees to Medicare.
ROMNEY: And the president supports taking dollar seven hundred
sixteen billion out of that program.
===================================
Event 2: [lines 6-8]
ROMNEY: So that's that's number one.
** ROMNEY: Number two is for people coming along that are young,
what <<I>> do to make sure that we can keep Medicare in
place for them is to allow them either to choose the
current Medicare program or a private plan.
ROMNEY: Their choice.
## Marker with two types (both: "I" & "you")
i_you_disc <- with(pres_debates2012, discourse_connector(dialogue, person,
names = c("I", "you"),
regex = list(
I = "I('[a-z]+)*\\b",
you = "(\\b[Yy]ou('[a-z]+)*\\b)"
),
terms = list(
I = c(" I ", " I'"),
you = c(" you ", " you'")
)
))
i_you_disc[[1]] person word.count I you
1 OBAMA 18317 330(1.80%) 252(1.38%)
2 ROMNEY 19923 505(2.53%) 227(1.14%)
3 CROWLEY 1670 49(2.93%) 73(4.37%)
4 LEHRER 765 9(1.18%) 36(4.71%)
5 QUESTION 583 18(3.09%) 22(3.77%)
6 SCHIEFFER 1445 25(1.73%) 61(4.22%)
head(i_you_disc[[2]])===================================
Event 1: [lines 2-4]
LEHRER: But what do you support the voucher system, Governor?
** ROMNEY: What <<I>> support is no change for current retirees and
near retirees to Medicare.
ROMNEY: And the president supports taking dollar seven hundred
sixteen billion out of that program.
===================================
Event 2: [lines 6-8]
ROMNEY: So that's that's number one.
** ROMNEY: Number two is for people coming along that are young,
what <<I>> do to make sure that we can keep Medicare in
place for them is to allow them either to choose the
current Medicare program or a private plan.
ROMNEY: Their choice.
head(i_you_disc[[3]])===================================
Event 1: [lines 1-3]
LEHRER: We'll talk about specifically about health care in a
moment.
** LEHRER: But what do <<you>> support the voucher system, Governor?
ROMNEY: What I support is no change for current retirees and near
retirees to Medicare.
===================================
Event 2: [lines 29-31]
OBAMA: That's what they do.
** OBAMA: And so <<you've>> got higher administrative costs, plus
profit on top of that.
OBAMA: And if you are going to save any money through what
Governor Romney's proposing, what has to happen is, is
that the money has to come from somewhere.
keyWords <- with(pres_debates2012, kwic(dialogue, list(time, person)))
plot(keyWords[[1]], high = "red")
with(pres_debates2012, plot(keyWords, grouping.var = person, rm.vars = time,
total.color = NULL, bg.color = "black", color = "yellow",
horiz.color="grey20"))
head(keyWords[[2]])===================================
Event 1: [lines 3-5]
time 1.ROMNEY: What I support is no change for current retirees
and near retirees to Medicare.
** time 1.ROMNEY: And the <<president>> supports taking <<dollar>>
seven hundred sixteen billion out of that program.
time 1.LEHRER: And what about the vouchers?
===================================
Event 2: [lines 9-11]
time 1.ROMNEY: They get to choose and they'll have at least two
plans that will be entirely at no cost to them.
** time 1.ROMNEY: So they don't have to pay additional money, no
additional <<dollar>> six <<thousand>>.
time 1.ROMNEY: That's not going to happen.