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Speaking out of turn: How video conferencing reduces vocal synchrony and collective intelligence


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Collective intelligence (CI) is the ability of a group to solve a wide range of problems. Synchrony in nonverbal cues is critically important to the development of CI; however, extant findings are mostly based on studies conducted face-to-face. Given how much collaboration takes place via the internet, does nonverbal synchrony still matter and can it be achieved when collaborators are physically separated? Here, we hypothesize and test the effect of nonverbal synchrony on CI that develops through visual and audio cues in physically-separated teammates. We show that, contrary to popular belief, the presence of visual cues surprisingly has no effect on CI; furthermore, teams without visual cues are more successful in synchronizing their vocal cues and speaking turns, and when they do so, they have higher CI. Our findings show that nonverbal synchrony is important in distributed collaboration and call into question the necessity of video support.
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Speaking out of turn: How video conferencing
reduces vocal synchrony and collective
Maria TomprouID
*, Young Ji Kim
, Prerna Chikersal
, Anita Williams Woolley
, Laura
A. Dabbish
1Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of
America, 2Department of Communication, University of California, Santa Barbara, Santa Barbara, California,
United States of America, 3Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh,
Pennsylvania, United States of America
Collective intelligence (CI) is the ability of a group to solve a wide range of problems. Syn-
chrony in nonverbal cues is critically important to the development of CI; however, extant
findings are mostly based on studies conducted face-to-face. Given how much collaboration
takes place via the internet, does nonverbal synchrony still matter and can it be achieved
when collaborators are physically separated? Here, we hypothesize and test the effect of
nonverbal synchrony on CI that develops through visual and audio cues in physically-sepa-
rated teammates. We show that, contrary to popular belief, the presence of visual cues sur-
prisingly has no effect on CI; furthermore, teams without visual cues are more successful in
synchronizing their vocal cues and speaking turns, and when they do so, they have higher
CI. Our findings show that nonverbal synchrony is important in distributed collaboration and
call into question the necessity of video support.
In order to survive, members of social species need to find ways to coordinate and collaborate
with each other [1]. Over a number of decades, scientists have come to study the collaboration
ability of collectives within a framework of collective intelligence, exploring the mechanisms
that enable groups to effectively collaborate to accomplish a wide variety of functions [26].
Recent research demonstrates that, like other species, human groups exhibit “collective
intelligence” (CI), defined as a group’s ability to solve a wide range of problems [2,3]. As
humans are a more cerebral species, researchers have thought that their group performance
depends largely on verbal communication and a high investment of time in interpersonal rela-
tionships that foster the development of trust and attachment [7,8]. However, more recent
research on collective intelligence in human groups illustrates that it forms rather quickly [2],
is partially dependent on members’ ability to pick up on subtle, nonverbal cues [911], and is
strongly associated with teams’ ability to engage in tacit coordination, or coordination without
PLOS ONE | March 18, 2021 1 / 14
Citation: Tomprou M, Kim YJ, Chikersal P, Woolley
AW, Dabbish LA (2021) Speaking out of turn: How
video conferencing reduces vocal synchrony and
collective intelligence. PLoS ONE 16(3): e0247655.
Editor: Marcus Perlman, University of Birmingham,
Received: August 5, 2020
Accepted: February 10, 2021
Published: March 18, 2021
Peer Review History: PLOS recognizes the
benefits of transparency in the peer review
process; therefore, we enable the publication of
all of the content of peer review and author
responses alongside final, published articles. The
editorial history of this article is available here:
Copyright: ©2021 Tomprou et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: The data of the study
are publicly available at
Funding: This material is based upon work
supported by the National Science Foundation
under grant numbers CNS-1205539 (url: https://
verbal communication [12]. This suggests that there is likely a so-called deep structure to CI in
human groups, with nonverbal and physiological underpinnings [12,13], just as is the case in
other social species [14,15].
Existing research suggests that nonverbal cues, and their synchronization, play an impor-
tant role in human collaboration and CI [10]. Nonverbal cues are those that encompass all the
messages other than words that people exchange in interactive contexts. Researchers consider
nonverbal cues more reliable than verbal cues in conveying emotion and relational messages
[16] and find that nonverbal cues are important for regulating the communication pace and
flow between interacting partners [17,18]. The literature on interpersonal coordination
explores many forms of synchrony [19,20], but the common view is that synchrony is
achieved when two or more nonverbal cues or behaviors are aligned [21,22]. Social psychology
researchers traditionally study synchrony in terms of body movements, such as leg movements
[23], body posture sway [24,25], finger tapping [26] and dancing [27]. These forms of syn-
chrony contribute to interpersonal liking, cohesion, and coordination in relatively simple tasks
[28,29]. Synchrony in facial muscle activity [30] and prosodic cues such as vocal pitch and
voice quality [3133] are of particular importance for the coordination of interacting group
members, as these facilitate both communication and interpersonal closeness. For example,
synchrony in facial cues has been consistently found to indicate partners’ liking for each other
and cohesion [30].
While humans in general tend to synchronize with others, interaction partners also vary in
the level of synchrony they achieve. The level of synchrony in a group can be influenced by the
qualities of existing relationships [34] but can also be influenced by the characteristics of indi-
vidual team members; for instance, individuals who are more prosocial [35] and more atten-
tive to social cues [10,36] are more likely to achieve synchrony and cooperation with
interaction partners. And, consistent with the link between synchrony and cooperation, recent
studies demonstrate that greater synchrony in teams is associated with better performance
Among the elements that nonverbal cues coordinate is spoken communication, particularly
conversational speaking turns, wherein partners regulate nonverbal cues to signal their inten-
tion to maintain or yield turns [39]. Conversational turn-taking has fairly primitive origins,
being observed in other species and emerging in infants prior to linguistic competence, and is
evident in different spoken languages around the world [40]. The equality with which interac-
tion partners speak varies, however, and those who do have more speaking equality consis-
tently exhibit higher collective intelligence [2,11]. The negative effect of speaking inequality
on collective intelligence has been demonstrated both in face-to-face and online interactions
The majority of existing studies on synchrony were conducted in face-to-face environments
[20,30,41] and focused on the relationship between synchrony and cohesion. We have a lim-
ited understanding of how synchrony relates to collective intelligence, particularly when group
members are not collocated and collaborate on an ad hoc basis -a form of modern organization
that has become increasingly common [42,43]. Given the exponential growth in the use of
technology to mediate human relationships [44,45], an important question is whether syn-
chrony in common, nonverbal communication cues in face-to-face interaction, such as facial
expression and tone of voice, still plays a role in human problem-solving and collaboration in
mediated contexts, and how the role of different cues changes based on the communication
medium used.
Researchers and managers alike assume that the closer a technology-mediated interaction is
to face-to-face interaction–by including the full range of nonverbal cues (e.g., visual, audio,
physical environment)–the better it will be at fostering high quality collaboration [4648]. The
Collective intelligence and non-verbal synchrony
PLOS ONE | March 18, 2021 2 / 14
1205539&HistoricalAwards=false) Author who
received the award: L.D., OAC-1322278 (url:https://
1322278) (Author who received the award A.W.),
and OAC-1322254 (url:.
(Author who received the award A.W.). The funders
had no role in study design, data collection and
analysis, decision to publish, or preparation of the
Competing interests: The authors have declared
that no competing interests exist.
idea that having more cues available helps collaborators bridge distance is strongly represented
in both the management literature [49,50] and lay theory [51]. However, some empirical
research suggests that visual cue availability may not always be superior to audio cues alone. In
the absence of visual cues, communicators can effectively compensate, seek social information,
and develop relationships in technology-mediated environments [5255]. Indeed, in some
cases, task-performing groups find their partners more satisfactory and trustworthy in audio-
only settings than in audiovisual settings [56,57], suggesting that visual cues may serve as dis-
tractors in some conditions.
Purpose of the study and hypotheses
The primary goal of this research is to understand whether physically distributed collaborators
develop nonverbal synchrony, and how variation in audio-visual cue availability during collab-
oration affects nonverbal synchrony and collective intelligence. Specifically, we test whether
nonverbal synchrony–an implicit signal of coordination–is a mechanism regulating the effect
of communication technologies on collective intelligence. Previous research defines nonverbal
synchrony as any type of synchronous movement and vocalization that involves the matching
of actions in time with others [23]. This study focuses on two types of nonverbal synchrony
that are particularly relevant to the quality of communication and are available through virtual
collaboration and interaction–namely, facial expression and prosodic synchrony. We hypothe-
size that in environments where people have access to both visual and audio cues, collective
intelligence will develop through facial expression synchrony as a coordination mechanism.
When visual cues are absent, however, we anticipate that interacting partners will reach higher
levels of collective intelligence through prosodic synchrony. It will also be interesting to see if
facial expression synchrony develops and affects collective intelligence even in the absence of
visual cues; if this occurs, it would suggest that this type of synchrony forms, at least in part,
based on similarity in partners’ internal reactions to shared experiences, versus simply as reac-
tions to partner’s facial expressions. If facial expression synchrony is important for CI only
when partners see each other, it would suggest that the expressions play a predominantly social
communication role under those conditions, and the joint attention of partners to these signals
is an indicator of the quality of their communication. To explore these predictions, we con-
ducted an experiment where we utilized two different conditions of distributed collaboration,
one with no video access to collaboration partners (Condition 1) and one with video access
(Condition 2) to disentangle how the types of cues available affect the type of synchrony that
forms and its implications for collective intelligence.
Participant recruitment and data collection
Our sample included 198 individuals (99 dyads; 49 in Condition 1 and 50 in Condition 2). We
recruited 292 individuals from a research participation pool of a northeastern university in the
United States and randomly assigned into 146 dyads (59 in condition 1 and 87 in condition 2).
Due to technical problems with audio recording, ten dyads had missing audio data in Condi-
tion 1 and 37 dyads in Condition 2 resulting in 62% valid responses. To test for possible bias
introduced by missing data, we conducted independent sample t-tests to assess any differences
in demographics between the dyads retained and those we excluded due to technical difficul-
ties; no differences were detected (see S1 Appendix). All signed an informed consent form.
The average age in the sample was 24.82 years old (SD = 7.18 years); Ninety-six participants
(48.7%) were female. The ethnic composition of our sample was racially diverse: 6.6% from
different races, 50% Asian or Pacific, 33% White or Caucasian, 7% Black or African American,
Collective intelligence and non-verbal synchrony
PLOS ONE | March 18, 2021 3 / 14
2.5% Latin or Hispanic. Carnegie Mellon University’s Institutional Review Board approved all
materials and procedures in our study. The participant in Fig 1 has provided a written
informed consent to publish their case details.
The procedure was the same in both conditions, except that in Condition 1 there was no
camera and participants could only hear each other through an audio connection. In Condi-
tion 2, participants could also see each other through a video connection. Both conditions had
approximately equal numbers of dyads in terms of gender composition (i.e., no female, one
female, only-female dyads). Each session lasted about 30 minutes. Members of each dyad were
seated in two separate rooms. After participants completed the pre-test survey independently,
they initiated a conference call with their partner. Participants logged onto the Platform for
Online Group Studies (POGS:, a web browser-based platform supporting syn-
chronous multiplayer interaction, to complete the Test of Collective Intelligence (TCI) with
their partner [2,11]. The TCI contained six tasks ranging from 2 to 6 minutes each, and
instructions were displayed before each task for 15 seconds to 1.5 minutes. At the end of the
test, participants were instructed to sign off the conference call. Participants were then com-
pensated and debriefed. The publication has created a laboratory protocol with DOI.
Collective intelligence. Collective intelligence was measured using the Test of Collective
Intelligence (TCI) completed by dyads working together. The TCI is an online version of the
collective intelligence battery of tests used by [2], which contains a wide range of group tasks
[11,58]. The TCI was adapted into an online tool to allow researchers to administer the test in
a standardized way, even when participants are not collocated. Participants completed six
tasks representing a variety of group processes (e.g., generating, deciding, executing, remem-
bering) in a sequential order (see study’s protocol). To obtain collective intelligence scores for
all dyads, we first scored each of the six tasks and then standardized the raw task scores. We
then computed an unweighted mean of the six standardized scores, a method adapted from
Fig 1. This flowchart illustrates the methodology used to transform the raw data of each participant into individual
signals or measures from which synchrony and spoken communication features are calculated.
Collective intelligence and non-verbal synchrony
PLOS ONE | March 18, 2021 4 / 14
prior research on collective intelligence [58]. Cronbach’s alpha for the reliability of the TCI
scores was .81.
Facial expressions. We used OpenFace [59] to automatically detect facial movements in
each frame, based on the Facial Action Coding System (FACS). We categorized these facial
movements as positive (AU12 i.e., lip corner puller with and without AU6 i.e., cheek raiser),
negative (AU15 lip i.e., corner depressor and AU1 i.e., inner brow raiser and/or AU4 i.e., brow
lowerer) or other expressions (i.e., everything else in low occurrence that may be random).
Facial expression synchrony of the dyad is a variable encoding the synchrony between the
coded facial expression signals of the partners.
Prosodic features. Prosodic characteristics of speech contribute to linguistic functions
such as intonation, tone, stress, and rhythm. We used OpenSMILE [60] to extract 16 prosodic
features over time from the audio recording of each participant. These features included pitch,
loudness, and voice quality, as well as the frame-to-frame differences (deltas) between them.
We conducted principal components analysis with varimax rotation and used the first factor
extracted, which accounted for 55.87% of the variance in the data. The first factor included
four prosodic features: pitch, jitter, shimmer, and harmonics-to-noise ratio. Pitch is the funda-
mental frequency (or F0); jitter, shimmer, and harmonics-to-noise ratio are the three features
that index voice quality [61]. Jitter describes pitch variation in voice, which is perceived as
sound roughness. Shimmer describes the fluctuation of loudness in the voice. Harmonics-to-
noise ratio captures perceived hoarseness. Previous research has also identified these features
as important in predicting quality in social interactions [62]. All features were normalized
using z-scores to account for individual differences in range. Speaker diarization was not
needed, as the speech of each participant was recorded in separate files.
Nonverbal synchrony. Fig 1 illustrates how the raw data of each participant was trans-
formed to derive individual signals or measures. These individual signals or measures were then
used to calculate dyadic synchrony in facial expressions and prosodic features, speaking turn
inequality, and amount of overall communication. We computed synchrony in facial expres-
sions (coded as positive, negative, and other in each frame) and prosodic features between part-
ners for each dyad, using Dynamic Time Warping (DTW). DTW takes two signals and warps
them in a nonlinear manner to match them with each other and adjust to different speeds. It
then returns the distance between the warped signals. The lower this distance, the higher the
synchrony between members of the dyad. Hence, we reversed the signs of the DTW distance
measure to facilitate its interpretation as a measure of synchrony. We use DTW instead of other
distance metrics such as the Pearson correlation or simple Euclidean distance because DTW is
able to match similar behaviors of different duration that occur a few seconds apart, which better
captures the responsive, social nature of these expressions (see comparison in Fig 2) For both
facial expressions and prosodic features, we calculated synchrony across the six tasks of the TCI.
Spoken communication. We computed two features of spoken communication: speaking
turn inequality and the amount of overall spoken communication in the dyad. In order to
compute features related to the number of speaking turns, we first identified speaking turns in
audio recordings of each dyad. All audio frames for which Covarep [63] returned a voicing
probability over .80 were considered to contain speech. We extracted turns using the following
process [64]. First, only one person can hold a turn at a given time. Each turn passes from per-
son A to person B if person A stops speaking before person B starts. If person B interrupts per-
son A, then the turn only passes from A to B if A stops speaking before B stops. If person A
pauses for longer than one second, A’s turn ends. When both participants are silent for greater
than one second, no one holds the turn. We heuristically chose the threshold of one second,
since the pauses between most words in English are less than one second [64]. To measure
speaking turn inequality, we computed the absolute difference between the total number of
Collective intelligence and non-verbal synchrony
PLOS ONE | March 18, 2021 5 / 14
turns of both partners in the dyad. To measure the amount of overall spoken communication,
we summed the total number of samples of speech (i.e., the amount of time each person spoke
with voicing probability >.80) of both partners in the dyad.
Social perceptiveness. At the beginning of the session, each participant completed the
Reading the Mind in the Eyes (RME) test to assess the participant’s social perceptiveness [65].
This characteristic gauges individuals’ ability to draw inferences about how others think or feel
based on subtle nonverbal cues. Previous research has shown that social perceptiveness
enhances interpersonal coordination [66] and collective intelligence [2,11]. The test consists
of 36 images of the eye region of individual faces. Participants were asked to choose among
possible mental states to describe what the person pictured was feeling or thinking. The
options were complex mental states (e.g., guilt) rather than simple emotions (e.g., anger). Indi-
vidual participants’ scores were averaged for each dyad. We controlled for social perceptiveness
in our analyses predicting CI, because it is a consistent predictor of collective intelligence in
prior work.
Demographics. We also collected demographic attributes such as race, age, education,
and gender for each participant. As our level of analysis was the dyad, we calculated race simi-
larity, age and education distance, and number of females in the dyad.
Table 1 provides bi-variate correlations among study variables and descriptive statistics. We
first examined whether collective intelligence differs as a function of video availability. An
Fig 2. Dynamic Time Warping (DTW) is a better measure of behavioral synchrony than Euclidean distance
because it is able to match similar behaviors of different duration that occur a few seconds apart.
Collective intelligence and non-verbal synchrony
PLOS ONE | March 18, 2021 6 / 14
independent samples t-test comparing our two experimental conditions (no video vs. video)
revealed that there was not a significant difference in the observed level of collective intelli-
gence (M
= -.07, SD
= .64; M
= .08, SD
= .53; t(97) = -1.23, p= .22). Fur-
ther, and surprisingly, the level of synchrony in facial expressions was also not significantly
different between the two conditions; dyads with access to video did not synchronize facial
expressions more than dyads without access to video (M
= -7614.80, SD
= 3472.92;
= -7248.58, SD
= 3167.11;t(97) = -.55, p= .56). By contrast, the difference in
prosodic synchrony between the two conditions was significant; prosodic synchrony was sig-
nificantly higher in dyads without access to video (M
= -.32, SD
= 1.18; M
.26, SD
= .72; t(97) = -2.95, p= .004).
Finally, partners’ number of speaking turns were significantly less equally distributed in
dyads with video than in dyads with no video (speaking turn inequality M
= 26.31, SD
= 22.96; M
= 9.14, SD
= 5.63; t(97) = 5.13, p= .000).
We further examined whether synchrony affects CI differently depending on the availability
of video. Though collective intelligence did not differ with access to video, nor did the level of
facial expression synchrony achieved, we found that synchrony in facial expressions positively
predicted collective intelligence only in the video condition (see Fig 3; the unstandardised coef-
ficient for the conditional effect = .0001, t= 2.70, p= .01, bias-corrected bootstrap confidence
intervals were between.0000 and.0001, suggesting that when video was available, facial expres-
sions play more of a social role and partners jointly attend to them. Furthermore, social percep-
tiveness significantly predicted facial expression synchrony in the video condition (r= .31, p=
.03), consistent with previous research [10], but not in the no video condition (r= -.17, p= .25).
In addition, in the sample overall we found a main effect of prosodic synchrony on CI; con-
trolling for covariates, prosodic synchrony significantly and positively predicted CI (b= .29,
p= .003). We wondered why prosodic synchrony was higher in the no video condition, so
we explored other qualities of the dyads’ speaking patterns, particularly the distribution in
Table 1. Correlation matrix for study variables and descriptive statistics.
1 2 3 4 5 6 7 8 9 10 11
1. Collective intelligence
2. Facial expression synchrony .16
3. Prosodic synchrony .29�� .02
4. Speaking turn inequality -.13 .10 -.35��
5. Overall spoken communication -.24-.05 -.10 -.11
6. Video condition -.12 -.05 -.28�� .46-.16
7. Social perceptiveness .33�� .08 .02 .03 .02 -.04
8. Female number .15 .04 .07 .00 -.09 .00 .20
9. Age distance -.15 -.04 -.04 .16 -.06 .36-.18 -.12
10. Ethnic similarity -.02 -.09 .00 -.02 .08 .05 -.22-.00 -.03
11. Education distance -.18 .10 -.19 .05 -.08 .05 -.19 -.00 .25.09
Minimum -1.64 -27428 -3.26 0 214221 0 17.5 0 0 0 0
Maximum 1.35 -1617 1.63 82 16575414 1 32.5 2 49 4 4
Mean .00 -7789.28 0 17.47 6765098.17 - 26.25 .98 5.64 .36 1.25
SD .58 4206.59 1 18.44 3520702.91 - 2.78 .83 7.59 .48 1.14
�� p<.01; N = 99 dyads.
Collective intelligence and non-verbal synchrony
PLOS ONE | March 18, 2021 7 / 14
speaking turns which, as discussed earlier, is an aspect of communication shown to be an
important predictor of CI in prior studies [2,11]. Speaking turn inequality negatively pre-
dicted prosodic synchrony, controlling for covariates (b= -.35, p= .001). Mediation analyses
showed that speaking turn inequality mediated the relationship between video condition and
prosodic synchrony (effect size = .26, and the bias-corrected bootstrap confidence intervals are
between.05 and.44). To test the causal pathway from video access to speaking turn inequality
to prosodic synchrony to collective intelligence, we formally tested a serial mediation model.
The serial mediation was significant (effect size = .05, and the bias-corrected bootstrap confi-
dence intervals are between -.09 and -.018 (see Fig 4).
That is, video access leads to greater speaking turn inequality and, in turn, decreases the
dyad’s prosodic synchrony, which then decreases the dyad’s collective intelligence (see also
Table 2). Note here that an analysis of reverse causality, predicting the speaking turn inequality
from prosodic synchrony, was not supported as an alternative explanation.
Fig 3. Interaction effects of facial expression synchrony and video access condition on collective intelligence.
Fig 4. Serial mediation analysis of the effect of video access on collective intelligence.
Collective intelligence and non-verbal synchrony
PLOS ONE | March 18, 2021 8 / 14
We explored what role, if any, video access to partners plays in facilitating collaboration when
partners are not collocated. Though we found no direct effects of video access on collective
intelligence or facial expression synchrony, we did find that in the video condition, facial
expression synchrony predicts collective intelligence. This result suggests that when visual
cues are available it is important that interaction partners attend to them. Furthermore, when
video was available, social perceptiveness predicted facial synchrony, reinforcing the role this
individual characteristic plays in heightening attention to available cues. We also found that
prosodic synchrony improves collective intelligence in physically separated collaborators
whether or not they had access to video. An important precursor to prosodic synchrony is the
equality in speaking turns that emerges among collaborators, which enhances prosodic syn-
chrony and, in turn, collective intelligence. Surprisingly, our findings suggest that video access
may, in fact, impede the development of prosodic synchrony by creating greater speaking turn
inequality, countering some prevailing assumptions about the importance of richer media to
facilitate distributed collaboration.
Our findings build on existing research demonstrating that synchrony improves coordina-
tion [30,33] by showing that it also improves cognitive aspects of a group, such as joint
Table 2. Summary of regression analyses for serial mediation.
Dependent Variable: Speaking turn inequality coefficient se t p 95% Confidence Intervals
Lower Bound Upper Bound
constant -.88 .91 -.97 .33 -2.69 .92
Social perceptiveness .02 .03 .59 .55 -.04 .08
Female number -.01 .11 -.14 .88 -.24 .20
Overall spoken communication -.03 .09 -.38 .69 -.22 .15
Video condition .92 .18 4.95 .00 .55 1.29
= .21, F(4,94) = 6.53, p = .001
Dependent Variable: Prosodic synchrony coefficient se t p 95% Confidence Intervals
Lower Bound Upper Bound
constant -.79 .94 -.83 .40 -2.67 1.08
Social perceptiveness .00 .03 .16 .87 -.06 .07
Female number .06 .11 .54 .58 -.16 .29
Overall spoken communication -.16 .09 -1.67 .09 -.35 .03
Video condition -.36 .21 -1.70 .09 -.79 .06
Speaking turn inequality -.28 .10 -2.63 .00 -.49 -.07
= .17, F(5,93) = 3.85, p = .003
Dependent Variable: Collective intelligence coefficient se t p 95% Confidence Intervals
Lower Bound Upper Bound
constant -1.90 .52 -3.63 .00 -2.95 -8.64
Social perceptiveness .06 .01 3.51 .00 .02 .10
Female number .02 .06 .45 .64 -.09 .15
Overall spoken communication -.14 .05 -2.58 .01 -.25 -.03
Video condition -.06 .12 -.54 .58 -.30 .17
Speaking turn inequality -.03 .06 -.63 .52 -.16 .08
prosodic synchrony .12 .05 2.23 .02 .01 .24
= .25, F(6,92) = 5.23, p =.001
Note. N = 99 dyads; Video condition coded as 1, No video condition coded as 0.
Collective intelligence and non-verbal synchrony
PLOS ONE | March 18, 2021 9 / 14
problem-solving and collective intelligence in distributed collaboration. Much of the previous
research on synchrony has been conducted in face-to-face settings. We offer evidence that
nonverbal synchrony can occur and is important to the level of collective intelligence in dis-
tributed collaboration. Furthermore, we demonstrate different pathways through which differ-
ent types of cues can affect nonverbal synchrony and, in turn, collective intelligence. For
example, prosodic synchrony and speaking turn equality seem to be important means for reg-
ulating collaboration. Speaking turns are a key communication mechanism operating in social
interaction by regulating the pace at which communication proceeds, and is governed by a set
of interaction rules such as yielding, requesting, or maintaining turns [18]. These rules are
often subtly communicated through nonverbal cues such as eye contact and vocal cues (e.g.,
back channels), altering volume and rate [18]. However, our findings suggest that visual non-
verbal cues may also enable some interacting partners to dominate the conversation. By con-
trast, we show that when interacting partners have audio cues only, the lack of video does not
hinder them from communicating these rules but instead helps them to regulate their conver-
sation more smoothly by engaging in more equal exchange of turns and by establishing
improved prosodic synchrony. Previous research has focused largely on synchrony regulated
by visual cues, such as studies showing that synchrony in facial expressions improves cohesion
in collocated teams [30]. Our study underscores the importance of audio cues, which appear
to be compromised by video access.
Our findings offer several avenues for future research on nonverbal synchrony and human
collaboration. For instance, how can we enhance prosodic synchrony? Some research has
examined the role of interventions to enhance speaking turn equality for decision making
effectiveness [67]. Could regulating conversational behavior increase prosodic synchrony?
Furthermore, does nonverbal synchrony affect collective intelligence similarly in larger
groups? For example, as group size increases, a handful of team members tend to dominate the
conversation [68] with implications for spoken communication, nonverbal synchrony, and
ultimately collective intelligence. Our results also underscore the importance of using behav-
ioral measures to index the quality of collaboration to augment the dominant focus on self-
report measures of attitudes and processes in the social sciences, because collaborators may
not always report better collaborations despite exhibiting increased synchrony and collective
intelligence [2,10]. Our study has limitations, which offer opportunities for future research.
For example, our findings were observed in newly formed and non-recurring dyads in the lab-
oratory. It remains to be seen whether our findings will generalize to teams that are ongoing or
in which there is greater familiarity among members, as in the case of distributed teams in
organizations. We encourage future research to test these findings in the field within organiza-
tional teams.
Overall, our findings enhance our understanding of the nonverbal cues that people rely on
when collaborating with a distant partner via different communication media. As distributed
collaboration increases as a form of work (e.g., virtual teams, crowdsourcing), this study sug-
gests that collective intelligence will be a function of subtle cues and available modalities.
Extrapolating from our results, one can argue that limited access to video may promote better
communication and social interaction during collaborative problem solving, as there are fewer
stimuli to distract collaborators. Consequently, we may achieve greater problem solving if new
technologies offer fewer distractions and less visual stimuli.
Supporting information
S1 Appendix. t-test results comparing cases with valid and missing data.
Collective intelligence and non-verbal synchrony
PLOS ONE | March 18, 2021 10 / 14
We thank research assistants Thomas Rasmussen, Brian Hall, and Mikahla Vicino for their
help with data collection. We are also grateful to Ella Glickson and Rosalind Chow for provid-
ing valuable feedback in earlier versions of this manuscript.
Author Contributions
Conceptualization: Maria Tomprou, Young Ji Kim, Prerna Chikersal, Anita Williams Wool-
ley, Laura A. Dabbish.
Data curation: Prerna Chikersal.
Formal analysis: Maria Tomprou, Young Ji Kim.
Funding acquisition: Anita Williams Woolley, Laura A. Dabbish.
Investigation: Maria Tomprou, Prerna Chikersal.
Methodology: Maria Tomprou, Prerna Chikersal.
Project administration: Laura A. Dabbish.
Resources: Anita Williams Woolley, Laura A. Dabbish.
Software: Prerna Chikersal, Laura A. Dabbish.
Supervision: Anita Williams Woolley, Laura A. Dabbish.
Writing – original draft: Maria Tomprou, Young Ji Kim, Prerna Chikersal, Anita Williams
Writing – review & editing: Maria Tomprou, Young Ji Kim, Prerna Chikersal, Anita Williams
Woolley, Laura A. Dabbish.
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... further showed that turn-taking's impact was amplified when it stepped outside of reporting relationships. Turn-taking is especially important in virtual, sensory-poor interactions (with and without video), as concludedTomprou et al. (2021). All of these researchers found that contribution equity and sequence could be influenced by facilitation or facilitative moves, such as time-keeping or shared goal referencing.McCardle-Keurentjes and Rouwette (2018) added that, relative to un-facilitated groups, facilitated groups had better content co-development sequencing or staging and collective discernment.Specifically, facilitation helped progress conversations through stages of content expansion, into sensemaking and deliberation:[f]acilitators mainly ask questions from the rational and social validation category, and this question type declines over the course of the discussion process. ...
Sustainability is a dynamic, multi-scale endeavor. Coherence can be lost between scales – from project teams, to organizations, to networks, and, most importantly, down to conversations. Sustainability researchers have embraced transdisciplinarity, as it is grounded in science, shared language, broad participation, and respect for difference. Yet, transdisciplinarity at these four scales is not well-defined. In this dissertation I extend transdisciplinarity out from the project to networks and organizations, and down into conversation, adding novel lenses and quantitative approaches. In Chapter 2, I propose transdisciplinarity incorporate academic disciplines which help cross scales: Organizational Learning, Knowledge Management, Applied Cooperation, and Data Science. In Chapter 3 I then use a mixed-method approach to study a transdisciplinary organization, the Maine Aquaculture Hub, as it develops strategy. Using social network analysis and conversation analytics, I evaluate how the Hub’s network-convening, strategic thinking and conversation practices turn organization-scale transdisciplinarity into strategic advantage. In Chapters 4 and 5, conversation is the nexus of transdisciplinarity. I study seven public aquaculture lease scoping meetings (informal town halls) and classify conversation activity by “discussion discipline,” i.e., rhetorical and social intent. I compute the relationship between discussion discipline proportions and three sustainability outcomes of intent-to-act, options-generation, and relationship-building. I consider exogenous factors, such as signaling, gender balance, timing and location. I show that where inquiry is high, so is innovation. Where acknowledgement is high, so is intent-to-act. Where respect is high, so is relationship-building. Indirectness and sarcasm dampen outcomes. I propose seven interventions to improve sustainability conversation capacity, such as nudging, networks, and using empirical models. Chapter 5 explores those empirical models: I use natural language-processing (NLP) to detect the discussion disciplines by training a model using the previously coded transcripts. Then I use that model to classify 591 open-source conversation transcripts, and regress the sustainability outcomes, per-transcript, on discussion discipline proportions. I show that all three conversation outcomes can be predicted by the discussion disciplines, and most statistically-significant being intent-to-act, which responds directly to acknowledgement and respect. Conversation AI is the next frontier of transdisciplinarity for sustainability solutions.
... For instance, video access may impede the development of prosodic synchrony when some communicating partners display visually salient social cues, thereby dominating the conversation. In such conditions, communication via audio-only channels can be more effective in synchronizing speaking turns [202]. Over the years, several studies have shown that mediated collaboration can lead to similar or even better performance than face-to-face collaboration. ...
Telemeetings such as audiovisual conferences or virtual meetings play an increasingly important role in our professional and private lives. For that reason, system developers and service providers will strive for an optimal experience for the user, while at the same time optimizing technical and financial resources. This leads to the discipline of Quality of Experience (QoE), an active field originating from the telecommunication and multimedia engineering domains, that strives for understanding, measuring, and designing the quality experience with multimedia technology. This paper provides the reader with an entry point to the large and still growing field of QoE of telemeetings, by taking a holistic perspective, considering both technical and non-technical aspects, and by focusing on current and near-future services. Addressing both researchers and practitioners, the paper first provides a comprehensive survey of factors and processes that contribute to the QoE of telemeetings, followed by an overview of relevant state-of-the-art methods for QoE assessment. To embed this knowledge into recent technology developments, the paper continues with an overview of current trends, focusing on the field of eXtended Reality (XR) applications for communication purposes. Given the complexity of telemeeting QoE and the current trends, new challenges for a QoE assessment of telemeetings are identified. To overcome these challenges, the paper presents a novel Profile Template for characterizing telemeetings from the holistic perspective endorsed in this paper.
... Der soziale Austausch sollte nicht nur zeitversetzt via E-Mail, sondern auch als Gespräch stattfinden, wobei mögliche Wirkungsunterschiede von Video-und Telefonkonferenzen zu berücksichtigen sind (Tomprou et al. 2021). ...
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Zusammenfassung Der Arbeits- und Gesundheitsschutz bei vorwiegend informationsverarbeitenden, geistigen Erwerbstätigkeiten – zunehmend mit digitalen Arbeitsmitteln und künstlicher Intelligenz – erfordert das Verwirklichen der Merkmale menschenzentrierter Arbeitsgestaltung (DIN EN ISO 6385/2016). Der Beitrag betrifft das menschzentrierte Gestalten des Arbeitsprozesses, nicht der Arbeitsmittel. Das Erfüllen dieser Merkmale soll nicht nur physische und psychische Beeinträchtigungen der Arbeitenden verhindern, sondern auch ihre Kompetenzen erhalten und erweitern sowie das gesundheitliche Wohlbefinden und die Arbeitsleistung fördern. Es werden übertragbare (generische) Vorschläge an die präventive, bedingungszentrierte und partizipative Gestaltung, insbesondere die Funktionsteilung zwischen Menschen und Technik und die Arbeitsorganisation/-teilung bei informationsverarbeitenden Tätigkeiten abgeleitet, die helfen, die Merkmale menschzentrierter Gestaltung zu erfüllen. Arbeitsschritte zur praktischen Verwirklichung sind skizziert. Eine Schwierigkeit beim Anwenden der Vorschläge ist ihre allgemeingültige Form. Sie erfordert das Übertragen auf die vielfältigen informationsverarbeitenden Arbeitstätigkeiten. Eine Hilfe bei ihrer Übertragung sind bewährte duale, partizipative und iterative Strategien der Automatisierung. Das Hauptanliegen ist zu verdeutlichen, dass und in welcher Hinsicht menschenzentrierte Arbeitsgestaltung auch bei vorwiegend informationsverarbeitenden, geistigen Erwerbstätigkeiten unerlässlich ist, und dass Digitalisierung diese präventive menschzentrierte Gestaltung nicht ersetzt, sondern voraussetzt.
... The study observed that groups interacted more cohesively, speaking out of turn less frequently, when there was a lack of video cues. As a result, teams were more successful in solving group problems, an ability known as Collective Intelligence (CI) [34]. In addition, Dennis et al. (2008), in their expansion on Media Richness Theory called Media Synchronicity Theory, push back on the idea that media richness is the ultimate quality for communication, concluding that there is no single media that is best for all tasks. ...
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In the design of qualitative interview studies, researchers are faced with the challenge of choosing between many different methods of interviewing participants. This decision is particularly important when sensitive topics are involved. Even prior to the Covid-19 pandemic, considerations of cost, logistics, and participant anonymity have increasingly pushed more interviews online. While previous work has anecdotally compared the advantages of different online interview methods, no empirical evaluation has been undertaken. To fill this gap, we conducted 154 interviews with sensitive questions across seven randomly assigned conditions, exploring differences arising from the mode (video, audio, email, instant chat, survey), anonymity level, and scheduling requirements. We surveyed interviewers and interviewees after their interview for perceptions on rapport, anonymity, and honesty. In addition, we completed a mock qualitative analysis, using the resulting codes as a measure of data equivalence. We note several qualitative differences across mode related to rapport, disclosure, and anonymity. However, we found little evidence to suggest that interview data was impacted by mode for outcomes related to interview experience or data equivalence. The most substantial differences were related logistics where we found substantially lower eligibility and completion rates, and higher time and monetary costs for audio and video modes.
... Nonetheless, this escalates the psychological burdens. 24,25 In our study, we also found that women were more prone to zoom fatigue. A high presence of zoom fatigue in women is also shown in some studies; for example, investigations in Sweden and the USA reported a 13.8% higher zoom fatigue proportion in women than in men. ...
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BACKGROUND: Global nations have enforced strict health protocols because of the COVID-19’s high transmission, infectivity, and mortality. As shown by increased online learning and video conferencing, the employment and education sectors are shifting to home-based activities. Video conferencing as a communication medium has subtly led to zoom fatigue. This study aimed to analyze the risk factors of zoom fatigue for early prevention and treatment. METHODS: This cross-sectional study was conducted on 335 Indonesian university students selected by purposive sampling in July 2021. Data were collected using a demographic questionnaire including online courses duration during the COVID-19 pandemic; Pittsburgh sleep quality index; depression, anxiety and stress scale-21; and zoom & exhaustion fatigue (ZEF) scale through Google Form (Google LLC, USA) distributed via social media and student forums. Association and correlation tests were used, and the model was developed using linear regression. RESULTS: The respondents were aged 21.3 (1.8) years with 12.8 (5.1) months of online courses during the COVID-19 pandemic and a ZEF scale of 2.8 (0.9). Students with higher ZEF had irregular physical exercise, poorer sleep quality, longer video conferencing sessions, longer months of courses during the COVID-19 pandemic, and higher mental illness (i.e., stress, anxiety, and depression). Smoking negatively correlated with fatigue (r = −0.12). The model for ZEF showed good predictability for zoom fatigue (p<0.001, R2 = 0.57). CONCLUSIONS: Daily exposure to video conferencing in educational settings throughout the pandemic has drastically increased zoom fatigue. The stakeholders must act immediately to minimize the risks while providing maximum benefits.
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In an attempt to curtail and prevent the spread of Covid-19 infection, social distancing has been adopted globally as a precautionary measure. Statistics shows that 75% of appointments most especially in the health sector are being handled by telephone since the outbreak of the Covid-19 pandemic. Currently most patients access health care services in real time from any part of the World through the use of Mobile devices. With an exponential growth of mobile applications and cloud computing the concept of mobile cloud computing is becoming a future platform for different forms of services for smartphones hence the challenges of low battery life, storage space, mobility, scalability, bandwidth, protection and privacy on mobile devices has being improved by combining mobile devices and cloud computing which rely on wireless networks to create a new concept and infrastructure called Mobile Cloud Computing (MCC). The introduction of Mobile cloud computing (MCC) has been identified as a promising approach to enhance healthcare services, with the advent of cloud computing, computing as a utility has become a reality thus a patient only pays for what he uses. This paper, presents a systematic review on the concept of cloud computing in mobile Environment; Mobile Payments and Mobile Healthcare Solutions in various healthcare applications, it describes the principles, challenges and opportunity this concept proffers to the health sector to determine how it can be harnessed is also discussed.
This article targets one of the fundamental changes in the judicial system induced by the severe limitations due to the absence of face-to-face meetings: the application of video conferencing in court sessions, an application with special requirements in this critical domain. A semi-structured literature review that we conducted revealed a lack of human-centered approaches. Potentials and challenges, mainly focused on the needs of judges, were also identified. These challenges were then transformed into requirements for designs of video conferencing systems in the judicial context. We ultimately developed a low-fidelity prototype of a system that incorporates a novel combination of three use-case-specific features: a solution to manage fatigue, a solution to manage user participation, and cognitive aid based on artificial intelligence (AI). The aim of the last feature was to reduce cognitive load while improving the moderation quality of court session leaders. Through a heuristic evaluation by human-computer interaction (HCI) and domain experts, the benefits of the basic design ideas, as well as potential areas for improvement, were identified. This paper presents the first systematic analyses of the potentials and limitations of video conferencing in German court sessions. It brings the enormous challenges of a critical domain in society, as well as human-centered and value-sensitive digitalization and AI adoption, under the spotlight.
Collective intelligence (CI) captures a team’s ability to work together across a wide range of tasks and can vary significantly between teams. Extant work demonstrates that the level of collective attention a team develops has an important influence on its level of CI. An important question, then, is what enhances collective attention? Prior work demonstrates an association with team composition; here, we additionally examine the influence of team hierarchy and its interaction with team gender composition. To do so, we conduct an experiment with 584 individuals working in 146 teams in which we randomly assign each team to work in a stable, unstable, or unspecified hierarchical team structure and vary team gender composition. We examine how team structure leads to different behavioral manifestations of collective attention as evidenced in team speaking patterns. We find that a stable hierarchical structure increases more cooperative, synchronous speaking patterns but that unstable hierarchical structure and a lack of specified hierarchical structure both increase competitive, interruptive speaking patterns. Moreover, the effect of cooperative versus competitive speaking patterns on collective intelligence is moderated by the teams’ gender composition; majority female teams exhibit higher CI when their speaking patterns are more cooperative and synchronous, whereas all male teams exhibit higher CI when their speaking involves more competitive interruptions. We discuss the theoretical and practical implications of our findings for enhancing collective intelligence in organizational teams.
Increasingly, organizational teams form quickly and change shape during their short lifespans, meaning they break from traditional definitions of “real” teams and experience instability in team membership and boundaries. While scholars have examined conditions that support effective teamwork in more-stable teams, we know little about how these dynamic teams can come to look like real teams that work interdependently rather than independently. My observations of and interviews with medical inpatient teams in a U.S. children’s hospital revealed a small subset of teams that succeeded at working interdependently within a core group (internally) and with a shifting set of peripheral contributors (externally). Brief periods of synchronous internal and external teamwork distinguished these emergently interdependent teams. To achieve these synchronous periods, core team members distributed their focus on internal team members and on peripheral members such as nurses, specialists, patients, and patients’ family members. Furthermore, core teams intertwined synchronous periods with cycles of external and internal coordination as team boundaries expanded and contracted. Such interdependence was associated with more-efficient work: faster morning rounds and, for patients, shorter hospital stays. Additionally, initial meetings among core team members set the stage for more-interdependent work. My findings contribute to dynamic teams research by illuminating the process of how teams can work interdependently as team boundaries expand and contract, to external activities research by suggesting that synchronous periods hold together previously documented cycles of separate internal and external activities, and to team launches research by extending work with more-stable teams to dynamic teams.
In investigating how member ability is translated into group brainstorming performance, it was predicted that a group’s collective intelligence (CI) would enable it to capitalize on member ability while maximizing process gains and mitigating process losses. Ninety-nine groups were randomly assigned to complete a short brainstorming task using a hybrid (individual-group work) or collective (only group work) task structure. High CI groups were better than low CI groups at translating member ability into group brainstorming performance. Additionally, this hybrid structure was more beneficial for low CI groups than for high CI groups in generating total ideas.
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Organizations are increasingly looking for ways to reap the benefits of cognitive diversity for problem solving. A major unanswered question concerns the implications of cognitive diversity for longer-term outcomes such as team learning, with its broader effects on organizational learning and productivity. We study how cognitive style diversity in teams—or diversity in the way that team members encode, organize and process information—indirectly influences team learning through collective intelligence, or the general ability of a team to work together across a wide array of tasks. Synthesizing several perspectives, we predict and find that cognitive style diversity has a curvilinear—inverted U-shaped—relationship with collective intelligence. Collective intelligence is further positively related to the rate at which teams learn, and is a mechanism guiding the indirect relationship between cognitive style diversity and team learning. We test the predictions in 98 teams using ten rounds of the minimum-effort tacit coordination game. Overall, this research advances our understanding of the implications of cognitive diversity for organizations and why some teams demonstrate high levels of team learning in dynamic situations while others do not.
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People influence each other when they interact to solve problems. Such social influence introduces both benefits (higher average solution quality due to exploitation of existing answers through social learning) and costs (lower maximum solution quality due to a reduction in individual exploration for novel answers) relative to independent problem solving. In contrast to prior work, which has focused on how the presence and network structure of social influence affect performance, here we investigate the effects of time. We show that when social influence is intermittent it provides the benefits of constant social influence without the costs. Human subjects solved the canonical traveling salesperson problem in groups of three, randomized into treatments with constant social influence, intermittent social influence, or no social influence. Groups in the intermittent social-influence treatment found the optimum solution frequently (like groups without influence) but had a high mean performance (like groups with constant influence); they learned from each other, while maintaining a high level of exploration. Solutions improved most on rounds with social influence after a period of separation. We also show that storing subjects’ best solutions so that they could be reloaded and possibly modified in subsequent rounds—a ubiquitous feature of personal productivity software—is similar to constant social influence: It increases mean performance but decreases exploration.
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Collective intelligence (CI), a group's capacity to perform a wide variety of tasks, is a key factor in successful collaboration. Group composition, particularly diversity and member social perceptiveness, are consistent predictors of CI, but we have limited knowledge about the mechanisms underlying their effects. To address this gap, we examine how physiological synchrony, as an indicator of coordination and rapport, relates to CI in computer-mediated teams, and if synchrony might serve as a mechanism explaining the effect of group composition on CI. We present results from a laboratory experiment where 60 dyads completed the Test of Collective Intelligence (TCI) together online and rated their group satisfaction, while wearing physiological sensors. We find that synchrony in facial expressions (indicative of shared experience) was associated with CI and synchrony in electrodermal activity (indicative of shared arousal) with group satisfaction. Furthermore, various forms of synchrony mediated the effect of member diversity and social perceptiveness on CI and group satisfaction. Our results have important implications for online collaborations and distributed teams.
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Prior research has shown that an individual's hormonal profile can influence the individual's social standing within a group. We introduce a different construct-a collective hormonal profile-which describes a group's hormonal make-up. We test whether a group's collective hormonal profile is related to its performance. Analysis of 370 individuals randomly assigned to work in 74 groups of three to six individuals revealed that group-level concentrations of testosterone and cortisol interact to predict a group's standing across groups. Groups with a collective hormonal profile characterized by high testosterone and low cortisol exhibited the highest performance. These collective hormonal level results remained reliable when controlling for personality traits and group-level variability in hormones. These findings support the hypothesis that groups with a biological propensity toward status pursuit (high testosterone) coupled with reduced stress-axis activity (low cortisol) engage in profit-maximizing decision-making. The current work extends the dual-hormone hypothesis to the collective level and provides a neurobiological perspective on the factors that determine who rises to the top across, not just within, social hierarchies.
Behavioral synchrony, physically keeping together in time with others, is a widespread feature of human cultural practices. Emerging evidence suggests that the physical coordination involved in synchronizing one's behavior with another engages the cognitive systems involved in reasoning about others' mental states (i.e., mentalizing). In three experiments (N = 959), we demonstrate that physically moving in synchrony with others fosters some features of mentalizing – a core feature of human social cognition. In small groups, participants moved synchronously or asynchronously with others in a musical performance task. In Experiment 1, we found that synchrony, as compared to asynchrony, increased self-reported tendencies and abilities for considering others' mental states. In Experiment 2, we replicated this finding, but found that this effect did not extend to accuracy in mental state recognition. In Experiment 3, we tested synchrony's effects on diverse mentalizing measures and compared performance to both asynchrony and a no-movement control condition. Results indicated that synchrony decreased mental state attribution to socially non-relevant targets, and increased mental state attribution to specifically those with whom participants had synchronized. These results provide novel evidence for how synchrony, a common feature of cultural practices and day-to-day interpersonal coordination, shapes our sociality by engaging mentalizing capacities.
Conference Paper
This paper introduces flash organizations: crowds structured like organizations to achieve complex and open-ended goals. Microtask workflows, the dominant crowdsourcing structures today, only enable goals that are so simple and modular that their path can be entirely pre-defined. We present a system that organizes crowd workers into computationally-represented structures inspired by those used in organizations - roles, teams, and hierarchies - which support emergent and adaptive coordination toward open-ended goals. Our system introduces two technical contributions: 1) encoding the crowd's division of labor into de-individualized roles, much as movie crews or disaster response teams use roles to support coordination between on-demand workers who have not worked together before; and 2) reconfiguring these structures through a model inspired by version control, enabling continuous adaptation of the work and the division of labor. We report a deployment in which flash organizations successfully carried out open-ended and complex goals previously out of reach for crowdsourcing, including product design, software development, and game production. This research demonstrates digitally networked organizations that flexibly assemble and reassemble themselves from a globally distributed online workforce to accomplish complex work.
As virtual teams are becoming more frequently implemented within organizations, research examining the effect of virtual tool use on team functioning has correspondingly expanded. One primary focus of this literature is the impact of virtuality on team communication. However, findings remained mixed. Specifically, the impact of virtuality on the mechanisms between communication and performance as well as the simultaneous moderating effect of contextual factors on this relationship remains to be fully examined. One reason for this lack of clarity stems from ambiguity regarding the elements that constitute communication. To address this gap, this paper delineates which aspects of communication are most influential and should, consequently, be the primary focus of future research efforts. An overarching framework of the communication process with accompanying research propositions is also described to inform future research and the practice of virtual teams.
Organizations are increasingly turning to crowdsourcing to solve difficult problems. This is often driven by the desire to find the best subject matter experts, strongly incentivize them, and engage them, with as little coordination cost as possible, to pool their knowledge. A growing number of authors, however, are calling for increased collaboration in crowdsourcing settings, hoping to draw upon the advantages of teamwork observed in traditional settings. The question is how to effectively incorporate team-based collaboration in a setting that has traditionally been individual-based. We report on a large field experiment of team collaboration on an online platform, in which incentives and team membership were randomly assigned, to evaluate the influence of exogenous inputs (member skills and incentives) and emergent collaboration processes on performance of crowd-based teams. Building on advances in machine learning and complex systems, we leverage new measurement techniques to examine the content and timing of team collaboration. We find that temporal "burstiness" of team activity and the diversity of information exchanged among team members are strong predictors of performance, even when inputs such as incentives and member skills are controlled. We discuss implications for research on crowdsourcing and team collaboration.
In spite of the increasing demand for virtual cooperation, still relatively little is known about the knowledge, skills, abilities, and other characteristics (KSAOs) individuals need for virtual teamwork. Thus, the current paper aims at synthesizing the existing literature into a comprehensive model of virtual teamwork KSAOs. To this end, we review (a) existing frameworks of KSAO requirements for virtual teamwork, (b) challenges posed by different facets of virtuality, and (c) KSAOs particularly relevant for meeting the identified challenges. The results of this review are integrated into a holistic model of virtual teamwork KSAOs with distal characteristics (personality, experience) and more proximal qualities (knowledge, skills, and motivation). Research gaps as well as avenues for future research will be outlined and applications for virtual team staffing and training will be discussed.