A Comparative Analysis of Actors' and Actresses' Oscar Acceptance
Speeches Based on Big Data Methodology
Liuchun Wen
Guangdong Technical College of Water Resources and Electric Engineering, Guangzhou, China
Keywords: Big Data Methodology, Oscar Acceptance Speech, Python Program, A Comparative Analysis.
Abstract: The adopted methods and instruments include SPSS analysis, EXCEL statistics, python program, etc. Based
on big data methodology, with the theoretical framework of Appraisal theory, the author makes a
comparative analysis of the Appraisal resources in the actors’ and actresses’ Oscar acceptance speeches and
their effects in realizing the Interpersonal function. The result of the study shows that both the Oscar
acceptance speeches from actors and actresses share the same distribution feature of the Appraisal
resources. The most frequently used ones are the Attitude resources, and the second are Graduation
resources and the third ones are Engagement. The current study has broadened the application of the
Appraisal theory. It proves that the Appraisal theory is applicable for the analysis of the field of Oscar
acceptance speeches, the sub-genre of public speeches.
1 INTRODUCTION
As is known to all, the representation of language
can be either in written form or in spoken form.
Brown and Yule list ten distinctive features "which
characterise spoken language"(1983:15). They point
out that the data of analysis of discourse should be
the language in use. The great differences between
spoken and written language result in great
distinctions between spoken and written discourse.
In Halliday’s Spoken and Written Language (1989),
he singled out the characteristics of spoken
discourse in terms of grammar, lexical, structure etc.
Generally speaking, spoken discourse tends to be
less informal than written discourse (Huang, 2001).
Halliday, the founder of Systemic Functional
Grammar (hereafter SFG), clearly states that his aim
of the construction of SFG is “to construct a
grammar for purposes of text analysis: one that
would make it possible to say sensible and useful
things about any text, spoken or written” (Huang,
2001: 29). He also explains that there are two levels
of discourse analysis: the lower level is to contribute
to the understanding of the text, and the higher one
is to the evaluation of the text. In this sense, the
application of SFG to the evaluative analysis of
spoken discourse is available.
According to Halliday’s SFG, language is
viewed as a way of making meaning and it has three
metafunctions: Ideational, Interpersonal and
Textual. As Chang (2004) points out, “In Halliday’s
model, the Interpersonal metafunction has to do
with how we use language to interact with other
people, to establish and maintain appropriate social
links with them, and to express our own attitude and
our evaluation of things or events in the world”.
Developed from SFG, Appraisal theory was set
up by Martin and his colleagues in the early 1990s
to extend the analysis of Interpersonal meaning from
a new perspective. There are three sub-systems of
Appraisal theory: Attitude, Engagement and
Graduation. Appraisal theory has been proved to be
a progress in discourse analysis as it has
incorporated the semantics of evaluation.
Appraisal theory has been effectively applied in
the analysis of different types of texts，including
spoken texts. There are, of course, many types of
spoken discourse. Huang (2001) states that in terms
of the form of discourse, spoken discourses include
everyday conversations, telephone talks, interviews,
public speeches, debates etc. So, public speech is
one important form among spoken discourses.
Public speeches are represented in various forms.
According to the field of public speech, it can be
divided into political speech, academic speech,
military speech, and so on. In recent years, many
Wen, L.
A Comparative Analysis of Actors’ and Actresses’ Oscar Acceptance Speeches Based on Big Data Methodology.
DOI: 10.5220/0011911700003613
In Proceedings of the 2nd International Conference on New Media Development and Modernized Education (NMDME 2022), pages 341-346
ISBN: 978-989-758-630-9
Copyright
c
2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
341
studies about political speeches have been carried
out from different linguistic perspectives. However,
few attempts have been made to the comparative
analysis of Oscar acceptance speeches (hereafter
OASs), a sub-genre of public speeches, within the
framework of Appraisal theory. This study will try
to fill this gap by employing the Appraisal theory as
the theoretical framework to make a comparative
analysis of the Appraisal resources in the actors’ and
actresses’ OASs and their effects in realizing the
Interpersonal function. We hope to find out if there
are any different Appraisal resources used by the
actors and actresses, although they have the same
goal to achieve, to express their strong feelings.
2 THE APPRAISAL ANALYSIS
OF THE OSCAR ACCEPTANCE
SPEECHES
the Appraisal theory is developed from the
Interpersonal metafunction within SFG. Ideational
metafuction, Interpersonal metafunction and Textual
metafunction are the three metafuctions.
we would analyse the ten OASs with the
theoretical framework of Appraisal theory. The
detailed analysis would be conducted from the
following four parts. The first part is the general
survey of the Appraisal resources in the actors’ and
actresses’ speeches. The second part to the fourth
part is to compare the actors’ and actresses’
speeches from the perspectives of the Attitude,
Engagement and Graduation systems and examine
the differences between them to explore the
underlying reasons.
2.1 The General Survey of the
Appraisal Resources in OASs
We have analysed the distribution of the Appraisal
resources in actors’ and actresses’ OASs, as is
shown in Table 1 and Table 2.
Table 1 The Appraisal Resources in Actors’ OASs
System Number Percentage (%) Ranking
Attitude 117 54.4 1
Engagement 22 10.2 3
Graduation 76 35.4 2
Appraisal 215 100
Table 2 The Appraisal Resources in Actresses’ OASs
System Number Percentage (%) Ranking
Attitude 93 44.7 1
Engagement 38 18.3 3
Graduation 77 37.0 2
Appraisal 208 100
Tables 1 and 2 show that in both the actors’ and
actresses’ OASs, there are almost the same amount
of Appraisal resources, 215 and 208. Both of them
have the most resources of Attitude in the three
subsystems and take up the biggest portion, up to
54.4% and 44.7%. The Graduation resources in
actors’ OASs are 76, taking up to 35.4%, ranking
the second, and in actresses’ OASs 77, 37.0%, and
also the second. The Engagement resources of both
are ranking the third, with 22 and 38, taking up the
percentages of 10.2% and 18.3%.
The statistics above indicates that both actors’
and actresses’ OASs employ three subsystems of the
Appraisal system, with the most abundant Attitude
resources. We would do further research on how the
three subsystems individually are involved in OASs.
Figure 1 Ideational, Interpersonal and Textual
metafunctions (Martin & White, 2008:8)
Figure 1 shows the interpersonal metafunction of
SFG. Ideational metafunction refers to the world
outside and inside of ourselves that we talk about,
presenting "our view of the world as consisting of
'going-on' (verbs) involving things (nouns) which
may have attributes (adjectives) and which go on
against background details of place, time, manner,
etc. (adverbials)" (Thompson, 2000: 76).
Interpersonal metafunction is concerned with
establishing and maintaining social relationships.
People can use languages to interact, to
communicate and to maintain and create social
relationships with each other. Textual metafunction
organizes the Ideational metafunction and
NMDME 2022 - The International Conference on New Media Development and Modernized Education
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Interpersonal metafunction into a coherent and
unified way in a text.
Martin and White further divide the Appraisal
theory into three subsystems: Attitude, Engagement
and Graduation. The overview of the Appraisal
resources is presented in Figure 2 (Martin & White,
2008: 38).
Figure 2 An Overview of Appraisal Resources
2.2 Analysis of Attitude in OASs
The potential goal of OASs is to let the winners
express their feelings that they are happy and
honored to accept the academic awards. Thereby,
we assume that most of the Attitude resources are
used to express their feelings and there are some
different ways of expressing that feelings between
actors and actresses. We have chosen five OASs
from actors and five from actresses. The analysis of
Attitude in this part is conducted by comparing the
employment of the three sub-systems of Attitude in
actors' and actresses' OASs.
In actors’ OASs, the general distribution of
Attitudinal resources is that Appreciation accounts
for 42.7%, ranking the first, and Affect 35.9%, the
second, and Judgement 21.4%, the third. In the five
OASs, 2 Affect, 3 Judgement and 1 Appreciation
are negative, while the rest of the Attitudinal
resources are positive. The negative resources are
listed as follows.
Affect
(1) For those who saw the signs of hatred as our
cars drove in tonight, I think that it is a good time
for those who voted for the ban against gay marriage
to sit and reflect and anticipate their great shame and
the shame in their grandchildren's eyes if they
continue that way of support. (M 3: 10)
Judgement
(2) I did not expect this, but I, and I want it to be
very clear that I do know how hard I make it to
appreciate me, often. (M 3: 3)
In Example (1), the actor uses the negative
Affect of "shame" to criticize those who voted for
the ban against gay marriage. The actor plays a
leading role in a movie about gay marriage, and by
this role, he wins the Oscar Actor in a Leading Role.
He loves the role he plays and supports the gay
marriage. By using the negative Affect of "shame",
he tries to align the potential audience who share the
same view and have the same positions.
In Examples (2), the actor makes negative
Judgement of himself to acknowledge others or
others’ supports.
We could generalize that although the actors use
all kinds of negative Attitudinal resources to express
their mixed and happy feelings at the time when
they receive the awards, all these resources can be
interpreted as positive ones.
the Affect resources in the five actresses' OASs
are 40, taking up to 43% in the three Attitudinal
resources, ranking the first. There are 29
Appreciation resources, with the proportion of
31.2%, which ranks the second. The least is
Judgement, with the number of 24, accounting or
25.8%. We could not find any negative Attitudinal
resources in the five actresses' OASs.
Figure 3 Judgement, Appreciation and Affect
By comparing the statistics in the two tables, we
note that there are two different figures in the two
different OASs.
The first one is that the ranking of the three
resources is different. In actors' OASs, the biggest
portion is the Appreciation resources, while in
actresses' OASs, the Affect resources occupy the
first place. It explains the fact that actors are more
rational than actresses when they receive awards and
make a speech on the stage. By employing
Appreciation than Affect resources, they are
expressing more feelings of assessment of objects,
A Comparative Analysis of Actors’ and Actresses’ Oscar Acceptance Speeches Based on Big Data Methodology
343
artefacts, processes and states of affairs than their
own inner feelings of emotions.
The second one is the distribution of negative
Attitudinal resources. There are several negative
resources in actors' OASs, while we could not find
any negative resources in actresses' OASs. It reflects
that actors are showing greater sense of humour than
actresses on the awarding-received stage. Because
all the negative resources can be interpreted as
positive ones. The negative usage of languages
reversely is one way of showing humour.
2.3 Analysis of Affect in OASs
Affect deals with utterances "which either convey(s)
a negative or positive assessment" or invite "the
reader to supply their own negative assessment"
(White, 2001:1). What is valued is the speakers' or
writers' emotional states. There are four sub-
categories in Affect, which are un/happiness,
in/security, dis/inclination and dis/satisfaction, as is
illustrated in Table 3. In this part, the author would
examine the distribution of the four categories in
both of the OASs.
Table 3 Distribution of Affect in Actors' OASs
Subsyste
m
Un/ha
ppines
s
In/securi
ty
Dis/satis
faction
Dis/incl
ination
Total
number
38 0 3 1
Percenta
ge(%)
90 0 7.5 2.5
+/- + - + - + - + -
Total
number
3
8
0 0 0 1 2 1 0
Percenta
ge(%)
9
0
0 0 0
2.
5
5
2.
5
0
Un/happiness, among the four categories, take
up the biggest proportion of 90%. There are thirty
eight out of forty two. All of them are positive
emotional feelings - happiness. In the five OASs,
the words which are used to express the authors'
gratitude should be pointed out particularly, in the
form of noun, verb, adjective or adverbial, such as
acknowledgement, thankful. In OASs, the speakers
try to align the potential audience and invoke the
audience's positive value toward the winners and the
ones who have helped them. The speakers also try to
align the ones who have helped the speakers by
mentioning their names for their contributions. For a
better understanding, we will list some examples to
be focused on.
(3) And finally, I want to thank my mom and my
dad; I want to thank my wife Keisha, my children,
my ancestors who continue to guide my steps, and
God, God who believes in us all and who's given
me this moment in this lifetime that I will hopefully
carry to the end of my lifetime into the next
lifetime. (M 1: 13)
(4) I wrote something down because I thought if
it would happen I would be a little overwhelmed
and I am. (M 1: 4)
The examples above demonstrate that the word
"thank" here is interpreted that the speakers like or
love someone so much that the speakers want to
express their positive emotion to the ones from
whom they get help or support. So the words of
"thank" are put into the category of un/happiness. It
shows their emotions of happiness. In the five
OASs, there are thirty positive words of "thank",
which are 78.9% of the un/happiness category.
there are three dis/satisfaction, with one positive
and two negative. There is one Dis/inclination,
which is positive. Dis/satisfaction deals with "our
feelings of achievement and frustration in relation to
the activities in which we are engaged" (Martin &
White, 2008: 50). Dis/inclination is irrealis Affect,
in which there is a Trigger.
(5) I'm very, very proud to live in a country that
is willing to elect an elegant man president and a
country who, for all its toughness, creates
courageous artists, and this is in great due respect
to all the nominees, but courageous artists who,
despite a sensitivity that sometimes has brought
enormous challenge, Mickey Rourke rises again and
he is my brother. (M 3: 13)
(6) For those who saw the signs of hatred as our
cars drove in tonight, I think that it is a good time
for those who voted for the ban against gay marriage
to sit and reflect and anticipate their great shame
and the shame in their grandchildren's eyes if they
continue that way of support. (M 3: 10)
Example (5) is the positive dis/satisfaction. By
expressing the feelings "proud" in relation to the
activity of being "in a country that is willing to elect
an elegant man president and a country who, for all
its toughness, creates courageous artists", the
speaker tries to align as many potential audience
who share the same view and take the same position
as possible.
By adopting the negative resources of
Dis/satisfaction in Example (6), the speaker tries to
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be distant from those who voted for the ban against
gay marriage.
2.4 Analysis of Graduation in OASs
As we introduced before in Chapter 3.3.3, the
system of Graduation deals with the gradability of
the other two systems of Appraisal theory: Attitude
and Engagement. Under Graduation, there are two
sub-systems, Force and Focus. In this chapter, we
are going to conduct a detailed analysis of the
distribution of these two sub-systems. We tend to
examine how the Graduation resources are used to
valuate the turning up or down Oscar winners'
positive or negative attitudinal feelings to intensify
the degree of their utterance. The general
distribution of the Graduation resources in actors'
and actresses' OASs are seen in Tables 4 and 5.
Table 4: The General Distribution of Graduation Resources in Actors' OASs
Force
Focus Up-scale
Down-
scale
Total
Intensifi-
cation
Quantifi-
cation
M 1 6 4 3 11 2 13
M 2 10 0 1 11 0 11
M 3 11 5 2 17 1 18
M 4 17 4 1 22 0 22
M 5 16 5 1 19 3 22
Total 50 18 8 70 6 76
Percentage 65.8% 23.7% 10.5% 92.1% 7.9% 100%
Table 5: The General Distribution of Graduation Resources in Actresses' OASs
Force
Focus Up-scale
Down-
scale
Total
Intensifi-
cation
Quantifi-
cation
Pr. 1 11 4 0 15 0 15
Pr. 2 5 0 2 7 0 7
Pr. 3 13 1 4 18 0 18
Pr. 4 9 6 1 16 0 16
Pr. 5 12 8 1 21 0 21
Total 50 19 8 77 0 77
Percentage 64.9% 24.7% 10.4% 100% 0 100%
From Tables 4 and 5, we could see that both of
the OASs have more Force resources than Focus
resources, and within Force resources,
Intensification accounts for more than
Quantification. Most of the resources are to up scale
the Attitude and Engagement resources.
3 CONCLUSION
In our research, we have selected ten pieces of
OASs of the recent years, five by leading actresses
and five by leading actors. In this thesis, because of
space limitation, we choose four pieces of OAS and
elaborate them. All of the pieces of OASs are
downloaded from the Internet through the homepage
of The Academy: http://www.oscars.org. Within the
framework of the Appraisal theory, through
qualitative approach, we have conducted a detailed
analysis of the four samples, trying to find out the
Interpersonal functions of OASs.
For the analysis of the Attitude resources in the
ten OASs, we note that there are two different
figures in the two different OASs.
The first one is that the ranking of the three
resources is different. In actors' OASs, the biggest
portion is the Appreciation resources, while in
actresses' OASs, the Affect resources occupy the
A Comparative Analysis of Actors’ and Actresses’ Oscar Acceptance Speeches Based on Big Data Methodology
345
first place. It explains the fact that actors are more
rational than actresses when they receive awards and
make a speech on the stage. They employ more
Appreciation than Affect to express more feelings of
assessment of objects, artefacts, processes and states
of affairs than their own inner feelings of emotions.
The second one is the distribution of negative
Attitudinal resources. There are several negative
resources in actors' OASs, while we could not find
any negative resources in actresses' OASs. It reflects
that actors are showing greater sense of humour than
actresses on the awarding-received stage. Because
all the negative resources can be interpreted as
positive ones. The negative usage of languages
reversely is one way of showing humour.
The Engagement resources employed in the
actors' and actresses' OASs are different. From
Table 4.10, it is evident that in actors' OASs, the
Dialogistic contraction and Dialogistic expansion
share almost the same proportion of Engagement
sources. Within the Dialogistic contraction, Deny
holds larger shares than other resources, and we
cannot find any Concur resources. In Dialogistic
expansion, all of the resources are Entertain, no
Attribute can be found. It shows that the actors pay
more attention to interaction with the audience as
well as to expressing his feelings.
The research on the Graduation resources clearly
shows that both of the OASs have more Force
resources than Focus resources, and within Force
resources, Intensification accounts for more than
Quantification. Most of the resources are to up scale
the Attitude and Engagement resources.
ACKNOWLEDGMENTS
The study is funded by 2021 Education and
Teaching Innovative Research Program in
Guangdong Technical College of Water Resources
and Electric Engineering: The Study of the Model of
Vocabulary Teaching in College English Based on
the Theory of Lexical Chunks (GX0205JGXM007)
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