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Review of  Television Dialogue


Reviewer: Jessie Sams
Book Title: Television Dialogue
Book Author: Paulo Quaglio
Publisher: John Benjamins
Linguistic Field(s): Discourse Analysis
Text/Corpus Linguistics
Book Announcement: 21.239

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Review:
AUTHOR: Quaglio, Paulo
TITLE: Television Dialogue
SUBTITLE: The Sitcom ‘Friends’ vs. Natural Conversation
SERIES: Studies in Corpus Linguistics 36
YEAR: 2009
PUBLISHER: John Benjamins

Jessie Sams, Department of English, Stephen F. Austin State University

SUMMARY
This book was published as the 36th volume in the series 'Studies in Corpus
Linguistics' by John Benjamins. As the title and subtitle suggest, Quaglio’s
primary goal is to compare dialogue from the sitcom “Friends” to natural
conversation (data for the latter are taken from the Longman Grammar Corpus).
Quaglio presents his quantitative analysis of the data in two distinct sections:
an analysis based on Biber’s (1988) Multidimensional analysis and a closer
analysis based on specific linguistic features.

Quaglio begins the introduction to his study by providing readers with a brief
overview of what his study will and will not be about. He states that while
some features of conversation analysis might be quite insightful, they were
beyond the scope of his present study. Such features include gender roles,
overlaps in conversations, in-depth analyses of natural conversation, and a
foray into examining terminology used in conversation analysis studies.
Instead, his focus is on analyzing TV dialogue in comparison with natural
conversation data. In order to do this, he uses two corpora: “Friends” data and
the Longman Grammar Corpus (LGC). For the “Friends” data, Quaglio uses “Biber
Tagger” and “Tag Count” software to annotate and quantitatively analyze the
data. Because the corpora are of different sizes (the “Friends” corpus has about
590,000 words—composed of transcripts from all episodes of the first nine
seasons—while the LGC has roughly 4,000,000 words), he also uses norming
procedures so that all comparisons of features are made per million words (e.g.,
X feature occurs Y times per 1,000,000 words).

Quaglio’s first data analysis is a cursory qualitative analysis to examine some
similarities and differences of the corpora. In his qualitative analysis, he
finds that the “Friends” corpus offers fewer types of settings and
interactions/topics than the LGC. In fact, he finds that the majority of the
“Friends” conversations take place in one of three settings (the coffee house,
Monica and Rachel’s apartment, or Joey and Chandler’s apartment) and focus
around the three recurring themes of “friendship, dating, and sex” (p. 47).

In the first section of the quantitative data analysis, Quaglio uses Biber’s
(1988) Multidimensional (MD) analysis to compare the “Friends” data to natural
conversation. Biber’s MD analysis originally looked at nine distinct genres,
comparing them across five different dimensions by using positive and negative
correlations of linguistic features. Quaglio primarily focuses on the first
dimension (D1), which is “involved vs. informational,” and compares the
“Friends” data to the “FACE-TO-FACE CONVERSATION” genre. Within the D1, involved
data is expected to have higher occurrences of such features as private verbs,
‘that’-deletion, present tense, and first- and second-person pronouns and fewer
occurrences of such features as nouns, large word lengths, and prepositions.
When comparing the “Friends” data to natural conversation, Quaglio finds that
the two corpora are actually quite similar with “Friends” having a mean score of
34.4 and Face-To-Face Conversation having a mean score of 35.3 on the D1 scale.
However, even though the mean scores are similar, the standard deviation for the
“Friends” data is much lower, reflecting the fact there is “much less variation
[in 'Friends'] than [in] conversation” (p. 65). This relates to Quaglio’s
qualitative analysis that showed “Friends” has fewer settings than natural
conversation and fewer possible participants. While “Friends” features the
same six characters, natural conversation is not limited in this way, resulting
in a variety of speakers’ ages and dialects.

In the second section of his quantitative analysis, Quaglio focuses on providing
a close analysis of four specific types of language often present in natural
conversation: vague, emotional, informal, and narrative language. In order to
analyze these aspects, he uses key linguistic features for each type of language
and analyzes the differences between the corpora, focusing on finding functional
reasons for those differences. He states that “the surprising similarities
between ‘Friends’ and natural conversation revealed by the multidimensional
analysis were the motivation for the second phase” of his analysis (p. 139). His
comparisons in this phase are frequency-based: He compares the features’
frequencies per million words in the LGC data and the “Friends” data.

The linguistic features Quaglio uses to identify vague language include hedges
(‘kind of,’ ‘sort of’), discourse markers (‘you know,’ ‘I mean’), and modals
(‘could,’ ‘might’). He finds that natural conversation has a tendency to include
more vague language than the “Friends” data. He points out, “Vagueness is less
desirable in ‘Friends,’ as the audience (the interlocutors of the show) cannot
interact with the characters” (p. 86). He shows that fewer occurrences of vague
language features can be directly related to the size of the audience and shared
background. While the characters within the show share common backgrounds, the
audience members watching the show do not necessarily share that background. And
while speakers in natural conversations tend to have small audiences, the
“Friends” characters were speaking for an audience of millions of viewers.

Emotional language includes linguistic features such as intensifiers (‘very,’
‘so’), expletives, emphatic ‘do,’ and slang terms (‘freak out,’ ‘screw up’).
Quaglio focuses on word choices for identifying emotional language, as his
corpora were not marked for prosody features; therefore, he did not quantify
features dependent on vocal quality. Surprisingly, “Friends” has higher
occurrences of the majority of emotional language markers than natural
conversations, including expletives. Although the “Friends” data has a higher
frequency of expletives overall, the two most common expletives found in natural
conversation (‘shit’ and ‘fuck’) are not found in “Friends” due to prime-time TV
restrictions. Quaglio relates the higher frequency of emotional language
features to the close relationships of the “Friends” characters; he states that
speakers with closer relationships tend to use more emotional language in their
conversations.

Quaglio identifies informal language by looking at features like expletives
(pointing out that some features are characteristic of more than one type of
language), vocatives (‘guys,’ ‘man,’ ‘bud’), and repeats (‘I-I-I’). His results
show that the “Friends” data has higher occurrences of informal language
features than the LGC data. He attributes this difference to three factors. The
first is the writers’ “attempt to make the language of ‘Friends’ credible and
authentic” (p. 120), resulting in “overcorrection” of what the writers expect in
natural conversation (p. 121). In other words, the writers try so hard to make
the language sound informal and natural that they go overboard and end up with
unnatural language use. The second is “the extremely close relationships shared
by the characters” (p. 120). Quaglio points out that his comparison between
corpora may have been different had he used a natural conversation corpus that
solely used data taken from conversations among close friends. And finally, the
last factor is “the creation of humor” in the “Friends” data (p. 120). The
writers of TV situation comedies have a specific goal in mind when writing the
character interactions: humor. They want to entertain audiences with language
choice while speakers of natural conversation do not always gear their
utterances toward creating humor (pp. 120-121).

The last type of language Quaglio analyzes is narrative language. In order to
compare the corpora, he uses the MD analysis, this time focusing on the second
dimension (D2): “narrative vs. non-narrative.” Narrative language frequently
includes linguistic features like past tense, third-person pronouns, and perfect
aspect. In all categories, natural conversation uses narrative language features
more frequently than “Friends” dialogue. Quaglio observes that this reflects the
frequency in which the “Friends” data is geared toward discourse immediacy
(i.e., focuses on “immediate concerns, facts, and evaluative utterances” (p.
137)). Natural conversation, on the other hand, is not as limited in terms of
the types of topics and interactions available to the speakers.

In his final chapter, Quaglio summarizes his analyses and provides implications
of and further applications for his study. He states that analyzing TV dialogue
provides insights typically not available for natural conversation, including a
diachronic approach (following the same characters’ speech over the course of a
show’s run) and an analysis of language change among a set group of speakers. In
particular, he points out that the “Friends” data showed the emergence of using
the intensifier ‘so’ to modify features beyond adjectives and adverbs (''Dude, we
are so gonna party!'', p. 144), and the many uses of ‘totally’ in conversation,
as in the following example (quoted on p. 143):

Chandler: That’s a great idea! We can easily think of a way for us both to enjoy
the room.
Monica: Totally!

He also looks at using TV dialogues in ESL classrooms as models of natural
conversation for language learners. He argues that while the dialogues can be
valuable tools in the classroom, the teachers should be aware of the differences
between TV dialogue and natural conversation and acknowledge those differences
for the benefit of the students.

EVALUATION

Quaglio’s study is thorough, well-thought out, and methodologically sound. He
acknowledges any shortcomings of the data and works to mitigate those
shortcomings to create strong analyses. One such example is the difference
between the size of the corpora: the “Friends” corpus is much smaller and
features six primary speakers; the LGC is much larger and features a variety of
speakers. Quaglio points this out wherever it affects outcomes (such as the
higher use of emotional language in “Friends”) and uses normed data for all
analyses (i.e., frequency per million words). His study opens the door to
discussions on humor (which he also suggests in his closing chapter), TV
dialogue in general, and genre studies. The layout of the book is
reader-friendly (complete with catchy chapter titles), and he presents an
in-depth linguistic analysis without overwhelming readers.

The only criticisms I have for this book are stylistic concerns. The first
concern is that the second chapter, which introduces the show “Friends” and its
cast of characters, offers a lot of information in a little space. Readers
unfamiliar with the show could become confused trying to keep the information
straight; a timeline of the show and a chart outlining key details for each
character would have been helpful to enhance the prose descriptions. The second
concern is that not all the dialogues or conversations presented in the book are
fully integrated into the prose. Dialogues/conversations are used to demonstrate
terms being discussed, but no explanation is offered for how those
dialogues/conversations actually portray that quality. Both concerns are only
relevant for readers unfamiliar with terminology used or situations/characters
discussed.

Overall, Quaglio presents a fascinating linguistic study that will appeal to
scholars with a wide range of interests: corpus linguistics, conversation
analysis, genre studies, language perception, and beyond.

REFERENCES
Biber, D. (1988). “Variation across speech and writing.” Cambridge University
Press.

Bright, K.S., Kauffman, M., & Crane, D. (Executive Producers). (1994).
Friends. [Television series] New York, National Broadcasting Company.
 
ABOUT THE REVIEWER:
ABOUT THE REVIEWER Jessie Sams is an Assistant Professor of Linguistics at Stephen F. Austin State University in Nacogdoches, TX. Her primary research interests include the intersection of syntax and semantics, genre studies based on linguistic features, and English quotatives.