35.2646, Review: Interactional Humor: Priego-Valverde (ed.) (2023)

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Subject: 35.2646, Review: Interactional Humor: Priego-Valverde (ed.) (2023)

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Date: 01-Oct-2024
From: Antonio Bianco [antonio.bianco1207 at gmail.com]
Subject: Anthropological Linguistics, Sociolinguistics: Priego-Valverde (ed.) (2023)


Book announced at https://linguistlist.org/issues/35.750

EDITOR: Béatrice Priego-Valverde
TITLE: Interactional Humor
SUBTITLE: Multimodal Design and Negotiation
SERIES TITLE: Language Play and Creativity [LPC]; Edited by: Nancy
Bell
PUBLISHER: De Gruyter Mouton
YEAR: 2023

REVIEWER: Antonio Bianco

SUMMARY

The volume (356 pages) comprises 11 chapters, each presenting a
distinct paper. The introduction – authored by the editor – provides a
general overview of the volume. The book is divided into two parts:
the first part (six chapters) focuses on face-to-face interactions,
while the second part (five chapters) examines humor in public
contexts (e.g., TV shows) and private mediated interactions (e.g.,
instant messaging apps).

The aim of the volume is to explore interactional humor – defined as
humor “influenced by the interaction in which it appears” (p. 2) –
across various interactional contexts, employing diverse methodologies
and data. This approach necessarily accounts for multimodality.
Consequently, the papers analyze not only linguistic, gestural,
prosodic, and facial movements, but also memes, gifs, and emojis
typical of social media interactions.

As outlined in the introduction, the volume addresses two central
questions that serve as the guiding thread of the work: “How is humor
multimodally produced, perceived, responded to, and negotiated?” (p.
2) and “What are the various multimodal resources involved in
interactional humor and how are they deployed?” (p. 6).

A detailed description of each of the 11 chapters follows. For each
chapter, the internal structure, goals, methodology, and results are
outlined.

Chapter 1 (A multimodal approach to children’s development of humor in
family life) – authored by A. Morgenstern, C. Dodane, and M.
Leroy-Collombel – presents a qualitative analysis of humor development
(linguistic, cognitive, and social) in two French-speaking children
under seven years old. T​​he interactions analyzed are drawn from the
Paris  Corpus (Morgenstern & Parisse 2012): a longitudinal corpus
including video recordings and transcriptions of spontaneous
adult-child interactions within family settings. The study explores
the stages of humor development, from children’s multimodal responses
to adult-initiated humor to their independent production of humor in
dialogues. It examines both the reception and production of amusement
and humor within a multimodal framework. The results indicate that
humor production begins as early as the second year of life (p. 33),
supported by parental participation in amusement contexts (p. 34) and
early exposure to humor. By age four, both children can produce and
engage in humorous exchanges using multimodal resources (i.e.,
prosodic patterns, gaze, gestures). Additionally, the analysis
(detailed in Section 4) is enhanced by figures illustrating multimodal
elements and spectrograms of laughter and speech from both parents and
children.

Chapter 2 (On target. On the role of eye-gaze during teases in
face-to-face multiparty interaction) – written by C. de Vries, B. Oben
and G. Brône – aims to fill a gap in the literature (p. 77) by
investigating gaze patterns during teases in interactions among
friends. It examines both internal teases, where the target is
present, and external teases, where the target is absent. The
theoretical background on teasing, the role of eye-gazes in
interactions, and specifically in teasing, is outlined in detail in
Section 2. The data, derived from the InSight Interaction Corpus
(Brône & Oben 2015), involve spontaneous triadic conversations (all
participants wore eye-tracking glasses). Guidelines for transcribing
conversations and annotating gazes and ironic teases are detailed in
Section 3. The data are analyzed both quantitatively, to examine gaze
distributions, and through micro-qualitative analysis of teasing
sequences.The study reveals the multifunctionality of eye-gazes in
interactions (p. 81) and identifies two distinct patterns. In external
teases, the speaker directs gazes between the addressees; in internal
teases, the target, who is more intensely gazed at by the speaker, is
also visually targeted. It is also worth noting that this study serves
as a strong foundation for further exploration of other
extralinguistic resources in teasing sequences (p. 81).

Chapter 3 (Humorous Smiling: A Reverse Cross-Validation of the Smiling
Intensity Scale for the Identification of Conversational Humor) –
authored by E. Gironzetti – presents a quantitative study to test
whether the Smiling Intensity Scale (SIS; Gironzetti et al. 2016) can
be used to identify the presence of humor in a multimodal corpus.
Sections 1 and 2 provide a description of the SIS and the relationship
between various smiling behaviors and conversational humor. The
analysis was conducted on two dyadic, semi-naturalistic,
computer-mediated conversations to identify, by applying the SIS,
moments in which speakers exhibit humor-related smiling behaviors (p.
87). The complex procedures for annotating  the smiling intensity and
instances of humor,  using ELAN (Wittenburg 2006), are described in
Section 3. The results reveal that SIS levels 2, 3, and 4 cannot be
considered reliable indicators for identifying humor in a
conversational corpus (p. 99). The study then concludes that smiling
intensity matching – i.e., when “two speakers synchronize their
smiling behavior at the same intensity level and at the same time” (p.
99) – is a more reliable tool for identifying humor. However, this
finding applies only to cases of affiliative humor, not to instances
of failed humor or disaffiliative humor, which were absent from the
analyzed corpus (p. 105).

Chapter 4 (Alternative conceptualizations of the Smiling Intensity
Scale (SIS) and their applications to the identification of humor) –
co-authored by H. Ergül, S. Miller, S. Attardo, and K. Kramer –
presents two developments (i.e., SIS-2 and SIS-3) of SIS-1 (Gironzetti
et al. 2016) that can be used without the complex training required
for the Facial Action Coding System (FACS, Ekman & Friesen 1978),
which underpins SIS-1. The chapter also provides a detailed
presentation of the FACS system and the SIS.

Specifically, SIS-2 involved creating “a photo scale representing the
SIS-1 descriptions by taking photos of individuals producing each of
the five SIS levels to” (p.115). This scale served as a basis for the
survey study. Using Qualtrics, participants were shown a photo  of a
person (representing each SIS level and other emotional states)
alongside the photo scale and asked to assess which image from the
scale best corresponded, in terms of the size of the smile, to the
presented photo (p. 115). This demonstrated that using a visual
comparison scale is a reliable tool for ratings of smiling intensity
(p.122)

The development of SIS-3 included two experiments. The first
experiment used a questionnaire (comprising yes/no questions) to test
whether participants, without knowledge of the SIS scale, could
analyze aspects of facial expressions ('Is this person laughing?', p.
9) in 28 presented photos.. The second experiment used the same type
of questionnaire, administered to a group of students, but with images
from video recordings of live interactions. In both cases, it was
found, with statistical significance, that yes/no questions can
replace the visual scale without losing reliability (p. 122).

Chapter 5 (Facial gestures and laughter as a resource for negotiating
humor in conversation) – penned by B. Priego-Valverde and S. Rauzy –
employs a mixed-methods approach, combining qualitative and
quantitative analyses, to examine the use of nonverbal behaviors
(smiles, neutral expressions, laughter) in 11 dyadic, face-to-face
interactions in French, drawn from the Cheese! corpus (Priego-Valverde
et al. 2020). The authors aim to identify general trends in nonverbal
behaviors during humorous sequences through statistical analysis,
while also gaining a deeper understanding of multimodal humor by
closely analyzing three examples.

A strength of this chapter is its detailed description of data
annotation protocols, including audio signals, instances of humor, and
facial gestures (using an extended version of the SIS, Gironzetti et
al. 2016). The quantitative analysis reveals three trends (p. 147):
laughter proportionally increases at the beginning of humorous
segments, peaking toward the end of the segment; speakers' smile
intensity increases approximately 6 seconds after the humorous
sequence starts; and about half of the humorous instances start with
neutral expressions. The qualitative analysis further elucidates the
role and specificity of these nonverbal behaviors in humor production
and negotiation; for instance, a neutral face can play a crucial role
in constructing a teasing sequence (p. 155).

Chapter 6 (Multimodal humor in human-robot interaction) – authored by
T. Kiderle, H. Ritschel, S. Mertes, and E. André – provides a detailed
overview of the state of the art in multimodal humor performance by
robots and outlines strategies (both verbal and non-verbal) to enhance
humor capabilities in humanoid robots. Initially, the chapter
discusses the main types of humor found in human conversations (e.g.,
canned humor, conversational humor) and summarizes the results of the
most significant studies on humor framing devices, with an emphasis on
irony markers. This section serves as a foundation for implementing
multimodal humor in robots. Subsequently, Section 4.1 reviews major
studies on comedy robots (e.g., Reeti robot, Weber et al. 2018) and
computational humor generators (e.g., STANDUP, Ritchie et al. 2006),
highlighting these systems' capabilities for dynamic content
generation.

Section 4.3 exemplifies techniques for using multimodal signals (e.g.,
gazes, vocal gestures, speech volume) to enhance the Reeti robot's
performance in producing canned humor and ironic statements. Notably,
the robot can produce ironic statements by reversing the polarity of
sentence elements (p. 193) and marking these statements with
linguistic signals (e.g., exaggerations or understatement), prosodic
signals, and non-verbal cues. Finally, the chapter underscores the
complex challenges in robot humor performance during bidirectional
communication with humans.

Chapter 7 (Facial expressions as multimodal markers of humor: More
evidence from scripted and non-scripted interactions) – written by S.
Tabacaru – examines the frequency and use of facial expressions,
particularly eyebrow movements, in various communicative contexts
(e.g., talk shows, TV series, interviews), for humorous purposes, with
a focus on sarcastic utterances. Drawing on Brône’s (2008) theory
(discussed in Section 2), facial expressions are treated as gestural
triggers marking the shift — central to humor’s surprise — between two
mental spaces: the discourse base space and the pretense space. The
chapter, specifically in Sections 2.1 and 2.2, analyzes both scripted
and non-scripted humor, using illustrative examples. It finds that
facial expressions, in combination with prosodic features and hand and
head gestures, delineate the transition between incongruous meanings
and mental spaces. In both contexts of humor, these expressions are
also useful for signaling the speaker's humorous intentions and
highlighting elements that enhance the common ground between
interlocutors. Additionally, Section 3 discusses how facial cues can
be misinterpreted by the audience as humorous, exceeding the speaker's
original intent.

Chapter 8 (Emojis and jocular flattery in Chinese instant messaging
interactions) – co-authored by J. Qiu, X. Chen, and M. Haugh –
investigates the role of emojis in jocular flattery sequences (Qiu et
al. 2021) in multi-party instant messaging interactions in Mandarin
Chinese. The chapter addresses two main questions: “(1) what roles do
emojis play in jocular flattery sequences?” and “(2) how does the use
of emojis in jocular flattery sequences vary with respect to the
footing of the participants?” (p. 237). The analysis utilizes episodes
of multi-party interactions on WeChat, encompassing 89 instances of
jocular flattery. The methodology for the analysis of emojis is based
on digital conversation analysis (e.g., Giles et al. 2015) and
multimodal discourse analytic research (e.g., Herring 2019).

Section 4 presents the results. In particular, Section 4.1 discusses
how emojis trigger jocular flattery. Indeed, emojis can make elements
more teasable, thus heightening the likelihood of jocular flattery.
They can also clarify the speaker’s humorous intent, prompting jocular
responses. Section 4.2 explores how emojis (e.g., laughing faces,
exaggerated emojis) index jocularity, marking teasing as laughable and
non-serious (p. 247), and how other emojis (e.g., clapping hands, red
roses) can amplify the jocular tone. Section 4.3, finally, examines
how emojis are used by humor targets to accept or reject jocularity
and by the audience to extend or continue jocular flattery sequences.

Chapter 9 (More than laughter: Multimodal humour and the negotiation
of in-group identities in mobile instant messaging interactions) –
penned by A. Sampietro – qualitatively analyzes the use of multimodal
elements in the production, negotiation, and response to humorous
messages within a WhatsApp group of 16 Spanish men, around 40 years
old. The study specifically focuses on humorous episodes characterized
by a visual component, even a single emoji. The data analysis, which
constitutes the bulk of the chapter, is divided into two parts. The
first section (Section 4.1) examines instances where one of the
participants deliberately initiates a humorous exchange, typically
using memes, funny photos, or laughing emojis as humor markers, as
well as cases where other users reframe a non-humorous message as
humorous. The second section (Section 4.2) considers responses to a
humor bid. Here, two trends emerge: minimal responses to humor – using
stickers, clapping hands, or interjections – and attempts to add more
humor, for example through the use of memes or other forms of teasing.

Additionally, the study lays the groundwork for future research
focused on a group chat composed of women and the analysis of humor in
other platforms (such as TikTok, Instagram, and Snapchat).

Chapter 10 (Humor and creativity in a family of strangers on Facebook)
– written by K. Mullan – investigates humorous multimodal posts,
manifestations of "everyday creativity" (Carter 2015), published in a
Facebook group of residents from a suburb in an Australian city. The
methodology of analysis (Section 2) combines both a macro-analytic
approach, to investigate interactional and social practices, and a
micro-analytic approach, to examine linguistic phenomena in detail.

Specifically, the chapter examines the use of puns, wordplay,
instances of joint fictionalization (cfr. Hay 2001), lexically
creative terms, and some of the most frequently discussed themes in
humorous exchanges. The discussion of each of these humor mechanisms
is developed across four sections. Thus, section 3.1 describes the use
of related sequences of puns (“ping-pong punning”, in Chiaro 2018) and
wordplay to create an atmosphere of conviviality, thereby maintaining
group cohesion. Section 3.2 discusses cases of online joint
fictionalizations, a form of humor based on the construction of absurd
scenarios that mock the shared rules of the group members. Section 3.3
investigates the terms of address (categorized and listed in a table)
used by group members, with particular attention to the use of
creative expressions that enhance personal relationships (p. 311).
Section 3.4, by analyzing three humorous posts related to the same
theme, highlights the importance of introducing recurring humorous
themes to reinforce the shared knowledge and unity of the group.

Chapter 11 (“Loanword translation and corrective acts are
incongruous”: Debating metapragmatic stereotypes through humorous
memes) – authored by V. Tsakona – analyzes a corpus of Greek memes
used to (humorously) express dissent towards translation practices
and/or the creation of Greek equivalents for specific English terms.
(e.g., delivery, takeaway, lockdown). These linguistic practices are
generally perceived as incongruous and, therefore, funny. The meme
analysis (Section 6) is preceded by five sections that delve into the
theoretical framework and methodology. Notably, Section 2 provides a
theoretical framework for metapragmatics (Verschuren 2000) and
"citizen sociolinguistics" (Rymes & Leone 2014), while Section 3
presents memes as vehicles for metapragmatic stereotypes (e.g.,
"grammar memes", White-Farnham (2019)). Section 4 reviews the debate
in Greece regarding the translation of English loanwords and Section 5
presents the Discourse Theory of Humor (Tsakona 2020) – the
theoretical framework for the analysis. The qualitative and
quantitative results (section 6) reveal that the rejection of
translation proposals and corrective actions (p. 333) is based on six
metapragmatic stereotypes. Each stereotype is examined through the
analysis of one or more memes, with a final table summarizing the
script oppositions and metapragmatic stereotypes of both citizen
sociolinguists and experts.

EVALUATION

This volume is undeniably relevant, intellectually stimulating, and
adept in achieving its objectives. However, the complex methodologies
employed and the topics covered make the book primarily aimed at humor
scholars (though not exclusively within the field of Linguistics).

One of the key strengths of the volume is its inclusion of chapters
that, even within the same section (e.g., face-to-face interactions),
analyze different types of corpora. This approach provides a
comprehensive view of interactional humor and enables the volume to
address its two central questions as thoroughly as possible. The use
of diverse corpora also allows the studies to consider multiple
languages, such as English, French, Greek, Spanish, and Chinese. This
diversity helps identify recurring patterns in the organization of
humorous sequences (p. 6) Moreover, the volume explores more "unusual"
contexts, within the analysis of interactional humor (p. 3). For
example, Chapter 6 examines humorous interactions between humans and
robots, while Chapters 2, 3, and 5 analyze semi-controlled corpora
(p.3), that require the use of new tools, such as eye-tracking
systems, video cameras, and annotation software.

Moreover, the second section of the volume is especially interesting
due to its analysis of data from instant messaging apps and social
media. These contexts provide, indeed, large datasets and enable the
exploration of how new multimedia resources (e.g., emojis, gifs,
memes) influence online humor and conversation management. As noted in
the introduction (p. 5), studying online interactions helps fill a gap
in humor studies by allowing longitudinal analysis of how humor
evolves over time within the same subjects and contexts.

With regard to the structure of the chapters, it is important to note
that most chapters present empirical analyses (e.g., 8-9-10), while
three chapters (3, 4, and 6) specifically focus on methodological
issues and the use of specific tools (e.g., SIS). However, every
chapter provides a detailed description of the methodology, annotation
protocols (especially in Chapters 2, 3, and 5), and theoretical
background.

Additionally, while many contributions (e.g., Chapters 7-9) adopt a
qualitative perspective with extensive example-driven analysis (p. 6),
Chapters 2, 3, and 5 provide quantitative analyses, reinforced by
statistical approaches (particularly in Chapters 2 and 5).

In summary, all these aspects reflect the complementary diversity and
the methodological synergy anticipated in the introduction (p. 6).
Additionally, the integration of these methodologies allows readers to
achieve a deep comprehension of the phenomena discussed in the volume
and to grasp their full complexities

Finally, the volume is significantly enhanced through the use of color
figures, detailed transcriptions of original data, and comprehensive
graphs and tables. These visual elements not only elucidate complex
results but also facilitate a clearer understanding of both
qualitative and quantitative results. For example, Chapter 6 includes
visual representations of the Reeti Robot’s facial movements and
Chapter 4 includes an appendix dedicated to compiling the images used
in the experiments.

In conclusion, it can be affirmed that future research on
interactional humor will benefit from the theoretical and
methodological models presented and discussed in this volume.

REFERENCES

Brône, Geert. 2008. Hyper and misunderstanding in interactional humor.
Journal of Pragmatics 40. 2027-2061.

Brône, Geert & Bert Oben.  2015. InSight Interaction: a multimodal and
multifocal dialogue corpus. Language Resources and Evaluation 49(1).
195-214.

Carter, Ronald. 2015. Language and Creativity: The Art of Common Talk.
London: Routledge.

Chiaro, Delia. 2018. The Language of Jokes in the Digital Age. London:
Routledge.

Ekman, Paul & Wallace V. Friesen. 1978. Facial action coding system.
Palo Alto: Consulting Psychologist Press.

Giles, David, Wyke Stommel, Trena Paulus, Jessica Lester & Darren
Reed. 2015. Microanalysis of online data: the methodological
development of digital CA. Discourse, Context and Media 7. 45-51.

Gironzetti, Elisa, Lucy Pickering, Meichan Huang, Ying Zhang,
Shigehito Menjo & Salvatore Attardo. 2016. Smiling synchronicity and
gaze patterns in dyadic humorous conversations. Humor - International
Journal of Humor Research 29(2), 301-324.

Hay, Jennifer. 2001. The pragmatics of humor support. HUMOR –
International Journal of Humor Research 14(1). 55-82.

Herring, Susan. 2019. The coevolution of computer-mediated
communication and computer-mediated discourse analysis. In Pilar
Gàrces-Conejos-Blitvich & Patricia Bou-Franch (eds.), Analysing
digital discourse. 25-67. Cham: Palgrave Macmillan.
Morgenstern, Aliyah & Christophe Parisse. 2012. The Paris Corpus.
French Language Studies 22(1). 7-12.

Priego-Valverde, Béatrice, Brigitte Bigi & Mary Amoyal. 2020. Cheese!:
A corpus of face-to-face French interactions. A case study for
analyzing smiling and conversational humor. Language Resources and
Evaluation Conference. 460-468. LREC2020, May 2020, Marseille, France.

Qiu, Jia, Xinren Chen & Michael Haugh. 2021. Jocular Flattery in
Chinese multi-party instant messaging interactions. Journal of
Pragmatics 178. 225-241.
Ritchie, Graeme, Ruli Manurung, Helen Pain, Annalu Waller & Dave
O’Mara. 2006. The standup interactive riddle builder. IEEE Intelligent
Systems 21(2). 67-69.

Rymes, Betsy & Andrea R. Leone. 2014. Citizen sociolinguistics: A new
media methodology for understanding language and social life. Working
Papers in Educational Linguistics 29(2). 25-43.

Tsakona, Villy. 2020. Recontextualizing Humor: Rethinking the Analysis
and Teaching of Humor. Boston: De Gruyter Mouton.

Verschuren, Jef. 2000. Notes on the role of metapragmatic awareness in
language use. Pragmatics 10(4). 439-456.

Weber, Klaus, Hannes Ritschel, Florian Lingenfelser & Elisabeth André.
2018. How to shape the humor of a robot - social behavior adaptation
based on reinforcement learning. In International conference on
multimodal interaction, 154-162. Boulder: ACM.

White-Farnham, Jamie. 2019. Resisting “Let's eat grandma”: The
rhetorical potential of grammar memes. Computers and Compositions 52.
210-221.

Wittenburg, Peter, Hennie Brugman, Albert Russel, Alex Klassmann &
Hans Sloetjes. 2006. ELAN: a Professional Framework for Multimodality
Research. In Proceedings of the Fifth International Conference on
Language Resources and Evaluation. Genoa, Italy: European Language
Resources Association.

ABOUT THE REVIEWER

Antonio Bianco is currently a Ph.D. candidate in Linguistic Sciences
at the University of Bergamo and at the University of Pavia. He earned
his master’s degree in Theoretical and Applied Linguistics from the
University of Pavia in 2022. His research interests focus on the use
of humor in political discourse, discursive implicitness and
(linguistic) persuasive strategies.



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