Modelling
social mobilisation – an interdisciplinary exploration
of twitter as a mediating tool for social acts and information networks
Dr
J.D.
Amor, Dr J. Foss, Dr G. Gkotsis, Dr H. Grainger-Clemson, E. Marchis, F.
Azhar
Abstract
In
recent years,
researchers, social commentators and the mass media have turned their
attention
to shifts in the use of social media for political and social action.
This
article provides an overview of the recent discussions focusing on how
Twitter
specifically functions as a mediating tool for social acts. We present
findings
from a recent pilot project exploring the mechanics of disseminating
information via Twitter across a dynamic human network in order to
contribute
to an understanding of how people use social media to share information
and
prompt others into action, and outline some approaches for performing
this
analysis. Taking the perspective of communities of users operating in
hybrid
spaces, we make recommendations for further research in this field.
Keywords
Twitter,
hybrid spaces, social networks, social acts, information flow
Introduction
We
are witnessing a paradigm change in collective
mobilisation ... from solidarity to fluidarity
...from collective mobilisation to the mobilisation of
a collective of
people and technologies ... a hybrid crowd. (Lasen & Martinez de
Albeniz,
2011:155)
In
recent years, researchers,
social commentators and the mass media have turned their attention to
shifts in
the use of social media for political and social action. Since its
launch in
2006, the microblogging platform ‘Twitter’ has become
increasingly popular and
powerful in assisting the ordinary person make public
‘acts’ of information
sharing and social commentary. Gillan and Merchant (2013) argue that it
has
achieved “a
new level of institutionalisation as it features in legal
cases, debates about privacy, and political intrigue” (2013:47).
In
its broadest sense, we conceptualise these social acts,
along with phenomena supported by social media such as flash mobs and
even more
violent happenings such as riots, as a form of desired social
‘mobilisation’.
The concepts of ‘hybrid spaces’ –
merging people, technologies, and online spaces - and
‘homophilly’ - the principle that we tend
to be similar to our friends - can offer a useful lens through which to
understand how people are persuaded to come together virtually and
physically.
In
this article, we discuss recent
literature that reveals recent perspectives on the role of social media
in
social networks and movements.Building on this, we discuss the
functions of
Twitter and the potential role it can play in mediating social acts and
find
that closer studies of the ‘Individual User – Tool
(Twitter) – Other User’
interface may contribute greatly to our understanding of the
possibilities for
this tool in social network formation and how individuals and
communities
collectively create meaning and make sense of the world around them. In
order
to provide a ‘real world’ example we present the
methodology and findings of a
recent empirical pilot study that created an open interactive Twitter
event on
a University campus giant video screen in order to investigate how
Twitter
functions as a mediating tool between direct human engagement and that
individual working within a group or ‘network’. We
intentionally created a
cross-discipline research team to bring a range of expertise and to
explore the
possibilities for a mixed methods approach, and we reflect this in the
format
of the article, through the collaborative authorship and through the
findings
that are based on qualitative data and computational modelling. We
conclude that effective ways of mapping a
social network can reveal its information flow, connectedness, and
communities,
as well as give a sense of more complex triangular relationships and
homophily By
combining a data-driven, network analysis approach with a
sociologically driven
qualitative analysis it is possible to derive a deeper insight into the
operation of a hybrid network than is possible through using one
approach in
isolation.
Recent
perspectives on the role of
social media in social networks and movements
The
forming of social networks
Social
networks can be defined as
“social structures that can be represented as...sets
of nodes (for
social system members) and sets of ties
depicting their interconnections” (Wellman and Berkowitz 1988,
cited in Zhao et
al 2011:5). Actors in a network can be individuals, groups or
organisations
that are connected in some way via certain relationships. However,
these
relationships do not exist in vacuum as we are located in different
places from
and to which we share information. This is what forms our
‘network society’
(Castells 2000). Our interaction with the external physical world is in
part
mediated by the technological tools we are both presented with and
choose to
carry about our person. Through our phones, tablets, and even simple
cameras
and music devices, we are able to reflect upon, capture, and connect
with a
place in a moment in time. Alternatively humans can make connections to
other
networks and be transported elsewhere or bring that other to where we
are (de
Souza e Silva & Delacruz 2006).
Social
media plays a dual role in
acts for social change: communication across the network of
participating
actors, but also sharing commentary across a wider network of
onlookers. It
comprises content, user communities and Web technologies, and networks,
which
mean that new ideas spread very quickly (Ahlqvist et. al. 2008). The
principle
that we tend to be similar to our friends
–‘homophily’ – is important in
determining the information that we are exposed to and share within
these
particular relationships; including as
friends on Facebook or followers on Twitter. Social selection –
the
circumstances that determine the people we are friends with - and
social
influence - the way we ‘fit in’ with these friends - play a
part in network
formation (Easley & Kleinberg 2010).Nevertheless, “a social
network exists
only if the users gain from cooperation and have the incentives to
interact
with one another. Therefore, to understand the necessary conditions for
the
formation of media-sharing social networks, we must investigate when
and how
users collaborate.” (Zhao et al 2011:167).
Due
to the membership of many
media-sharing social networks being voluntary and unregulated, the
‘connectivity’ or degree of connection between the
multiplicity of
communication networks can be varied (Kluitenberg 2006).The
users’ cooperation
cannot be guaranteed, giving rise to potential strategies employed by
others to
encourage such cooperation (Zhao et al 2011). Without any explicit
attempt by
the user, neighbour-copying can still occur where the individual mimics
the
behaviour of the closest individual.In everyday decision-making an
information
cascade occurs when people observe the actions of others and then make
the same
choice that the others have made, independently of their own private
information signals.
Types
of social acts
Gillan
and Merchant (2013) define some of the key ways Twitter is used based
on their
dual autho-ethnography: citizen
journalism, political activism, maintaining a fan-base, event
back-channel,
corporate advertising, service marketing, crowd-sourcing, informal
social-networking, and ambient sociability (alone but communicating
with
friends). Murthy
stresses that activism needs strong ties not
weak ones and “Twitter is about loose networks of
‘followers’ rather than a
structured organisation with leadership” (Murthy
2013:101),although here he is
talking about large scale political movements rather than the social
media-organised publicity ‘flash mobs’ we might be
accustomed to in town
centres. A closer study of the‘Individual User – Tool
(Twitter) – Other User’
interface may contribute greatly to our understanding of the
possibilities for
this tool in social network formation and how individuals and
communities
collectively create meaning and make sense of the world around them.
The
role of twitter as a mediating
tool for social acts
Hybrid
network society and
invisible technology
Where
technology and communication
networks are interwoven with social and political functions, a
‘hybrid space’
is created (Kluitenberg 2006). However, the technology potentially
becomes
invisible as it disappears from people’s awareness, due to its
frequent use and
embedding in our everyday acts and the small and subtle appearance of
the
physical devices and the physical action required to control them.
Manovich
(2002) argues that spaces are continually enriched with technology, but
only
become activated or ‘augmented’ when a specific function is
required, for
example, one engages with other spaces through a wireless connection.
Nevertheless, this human action, although utilising the Web, will also
rely on
the importance of (occupying) physical space (Jurgenson, 2011: 86).
Heidegger
(1977) conceptualises
technology as a “man-made means to an end established by
man”. By
conceptualising the human-tool interface as operating in a hybrid
space, we are
moving towards an understanding of communication and public
‘voice’ not so much
objectively mediated by tools but as human social acts taking place in
the same
virtual reality space as the mundane and everyday acts that are shared
and
commented on by individuals and their ‘friends’. This
blurring of boundaries is
an important element to consider in studies of the nature of
interaction via
social media.
The
functions of Twitter and the user
interface
Twitter
is a micro-blogging service
that allows users to post updates of a maximum length of 140
characters, published
in reverse chronological order on their Twitter homepages. The posts -
‘Tweets’
- are intended as a response to the question “What’s
happening?” This public
response hints at a broader social commentary than its Facebook
counterpart
status update that asks “What are you doing?” or “How
are you feeling?” Twitter
can also be used to share photos and links to other sites, as a way of
disseminating information in other forms than the simple 140-character
Tweet.
The user is asked three basic to-dos. Tell us what you’re doing,
find some
friends and follow what they’re doing, and turn on your mobile
phone to update
your friends on the go. In general, Tweets can be seen by all users on
the
medium rather than being restricted to one’s friends - anyone can
instantly see
a Tweet and respond to it (Murthy 2013).
One does not need to ‘know’ the other user or have
their permission to
direct a Tweet at them, although optional anonymity and private
accounts are built
into the system.
Term |
Meaning |
@ /
at-mention |
DirectsTweets
to certain users |
DM /
direct message |
A private
Tweet between two individuals (not published) |
Follower |
Another
user who has elected to follow the user |
Hashtag |
Topic
classifier; # placed before any text means a user can link their
Tweetto a larger conversation on the same topic |
Profile |
Homepage
equivalent with user information, followers, following and published
Tweets |
Reply Tweet |
ATweet
which replies to another user(s) directly via @ |
RT /
Retweet |
ForwardedTweets,
written by others, viewable by followers. |
Timeline |
Real-time
display of all Tweets of user and those followed |
Trending
topics |
Most
popular hashtags at any time. |
Tweet |
A message;
restricted to 140 characters and publically available(even without
having a Twitter account) |
Table
1 –
Glossary of Twitter terms.
Perceiving
Tweets as mere
superficial chat does not take into account the human creativity that
takes
place when discussions and information are combined and shared by users
to create
new meaning (Murthy 2013). Sturken & Thomas (2004) draw our
attention to
the user’s own perceptions of the social media tool they are
using as being
relevant to the functioning of the tool:
People
assign symbolic meanings to technologies. The
messages we communicate about technology are reflective,
revealing as much about the communicators as they do
about the technology. (Sturken & Thomas 2004, cited in Baym 2010:23)
The
dialogue between Twitter users
occurs through the at-sign - @ - before another user’s profile
name to direct a
Tweet at someone specific. Tweets can also be categorised by a
‘hashtag’. Any
word(s) preceded by a hash sign - # - through which the post of
strangers are
linked together, becoming included into a larger
‘conversation’ consisting of
all Tweets with the same hashtag (Murthy 2013).The hashtagis a key
function in
the construction of networks, information cascade, and the possibility
for
collective social acts, as “conversations are created more
organically...the
discourse is not structured around directed communication between
identified
interactants. It is more of a stream, which is composed of a polyphony
of
voices all chiming in” (Murthy 2013: 3-4).
Also
important is the function of
the Retweet – the forwarding of Tweets written by others to
one’s followers.
Murthy (2013) notes that this action attributes the Tweet to the
retweeter,
embedding the post in their profile and clearly labelled as such with
the
letters RT. This has a bearing on the meaning created: the information
is not
only shared as in ‘passed along´but is given extra weight
or voice by being
posted by another, and is also attributed to that new individual with
their own
unique set of views, values, and
followers.
Figure
1 - The Twitter profile page
of TEDxWarwick, showing the use of @, #, and RT. Accessed 21/8/13
Awareness
of audience
There
is a stageat which individual
users progress from not only controlling a new interface such as
Twitter, to comprehending
the social dimension inscribed in and enabled by its interface (Herwig
2009).Given
the public reach of Twitter, it is not just the actual number of
followers but
the user’s own perception of the anonymous others that may read
and even
retweet their original content that has a bearing on their sense of
wider
audience and agency in having a public voice. This is compared
toFacebook where
the user’s number of friends “provides material evidence
for the success and
status of that user’s constructed identity” (Charles
2012:123). Twitter
networks often formed around an event of particular interest, such as a
TV
talent show or a sports match, where the stars are ‘spoken
to’ by the ordinary
user or the broadcaster highlights pertinent content. Here it is
possible to
cross a boundary and make visible and physical what is usually only
virtual as
a form of ‘telepresence’ – a term attributed to
Minsky (1980) the founder of
MIT’s artificial intelligence laboratory, which refers to the
user’s perception
that they are interacting with other humans as if in the same space.
Methodological
approaches for
research in tracking and analysing social acts via twitter
Generating
data from Twitter
Tweets
can be analysed in two
distinct ways: firstly, Tweets can be analysed as individual objects
with word
and function content, such as Kouloumpis et al (2011), who found that
the
Twitter features – hashtags, emoticons, and intensifiers (such as
exclamation
marks) – were more useful than the word content in tracking
sentiment. Secondly
they can be analysed as objects that are taken up by another user
– either by
retweeting or the adoption of hashtags.
A
number of large scale studies
have taken place over the last few years, and whilst their results are
perhaps not
dramatically different to what one might expect, they provide important
evidence and tested methodological approaches for future research in
this area.
Suh et al (2010) used
a dataset of 74 million Tweets
to identify factors associated with retweet rate, also building a
predictive
retweet model. They found that URLs and hashtags have strong
relationships with
‘retweetability’. Perhaps unsurprisingly the number of
followers, as well as
the age of the account, seems to affect retweetability, although the
number of
past Tweets does not predict retweetability of a user's Tweet.
Romero
et al (2011) collected over
3 billion messages over 6 months from more than 6 million users,
analysing
sources of variation in how the most widely-used hashtags on Twitter
spread
within its user population. They found that sources of variation in
hashtag use
“involve not just differences in the probability with which
something spreads
from one person to another...but also differences in a quantity that
can be
viewed as a kind of ‘persistence’, the relative extent to
which repeated
exposures to a piece of information continue to have significant
marginal
effects on its adoption.” (2011:1). Hashtags that were more
politically
controversial were particularly persistent, in contrast to those
created within
the Twitter conversational style of words joined together, such as
#itsalwaysme. Romero et al concludes by saying that “some of the
most
significant differences in hashtag adoption provide intriguing
confirmation of
sociological theories developed in the off-line world” (2011:8)
such as
‘complex contagion’, relating to repeated exposure to
ideas, particularly those
that are contentious. This is consistent with other research and
literature
that acknowledge the subjectivity and the motivation of the user,
influencing
their interaction with spaces, communities, and the tool itself. They
make
strong recommendations for further study including:
‘homophilly’ and
influencing behaviours across topics and categories; and a more
fine-grained
analysis of a population at the individual level to contribute more
detailed
user-level data to the emerging body of broader studies.
Our
pilotstudy
The
pilot study we report on here took these key points from the review of
literature and previous research studies as its starting point. We
specifically
aimed to explore how network links are created and reinforced at a more
detailed user level, namely:
·
How
Tweets function as public social
acts in hybrid (on and offline) spaces
·
How
information propagates between
smaller communities of users across a wider network
·
How
computational analysis can be used
to model hybrid (human-technology) social networks
The
research required an interdisciplinary approach in its methodology.
Operating
from a new user account, we created the hashtag ‘#wj25’that
when used on a
designated day, would allow a Tweet to be projected onto a giant public
screen
in a main campus thoroughfare. The giant screen was situated just
behind an
outdoor performance venue during the Student Arts Festival. The hashtag
and
screen combined to offer an incentive for participants to post as well
as
explore notions of wider public audience. The hashtag also gave a
single
indicator for gathering Tweets relevant to the ‘event’ (the
live screen).
Mapping
Social Networks
Online
Social Networks are
particularly suited to computational modelling as the users and
communication
between them can be readily captured and analysed.
Such an analysis can be split into two parts,
structure and information flow, but the two are intrinsically linked.
The
principal idea behind analysing the structure of an Online Social
Network is to
identify the shape of the network; that is, to identify the users and
the
connections between them. In the case of Twitter this could look at
followers
and direct messages.
Once
the shape and layout of the
network has been identified, subsequent analysis can go in a number of
directions. One analysis would be to identify sub-groupings or
‘communities’ of
users. We define ‘communities’ as “groups
of related nodes that correspond to functional subunits such
as…social
spheres,” (Ahn et al 2010).
Furthermore, we are interested
insuch groups that have a large number of intra-connections but few
connections
to other sub-groups. A second form of analysis is to identify the
important
nodes in the network (see Tang et al 2010). In the case of Twitter this
could
help identify highly influential users: users whose Tweets reach a
large number
of people or who serves to transfer information from one sub-group to
another.
The
common abstraction in the
literature for analysing the flow of information and ideas is the
concept of
influence and idea adoption (Cosley et al 2010). A user in the network
is
exposed to a number of ideas and can either adopt an idea or not.
Additionally
each user is influenced by its neighbours and influences them in turn.
In the
case of Twitter, this form of analysis could be used to look at how
Retweets
propagate around a network or how the use of hashtags propagates over
time but
could additionally be extended to look at the actual content of the
Tweet for
particular words or meaning.
In
our pilot study, the architecture of the monitoring software was based
on a
client-server model with database storage. The server used the Twitter
streamingAPI to continuously search for Tweets containing
‘#wj25’. Each Tweet
was added to a moderation queue¸allowing a member of the team to
either publish
the Tweet or keep it hidden if it contained offensive content. Each
Tweet was
given a score depending on the number of hashtags (#), mentions (@) and
Retweets
(RT).
Every
14 seconds the two highest scoring Tweets were chosen for display based
on a
formula[1].
Whilst
the screen and Twitter feed was ‘live’, two members of the
research team
observed the actions of people in a thoroughfare space near the screen,
in
particular the Arts Festival performance area, and approached
individuals to
complete a survey questionnaire.
Using
a cross-discipline methodology, there a number of initial findings that
respond
to key areas identified in the literature: hybrid (people, technology,
and
event/place) spaces and telepresence; homophilly and network
connections; and different
types of activity.
By
collecting Tweets and noting the followship of the participants in the
‘#wj25’
event, a database was constructed and used to recreate the network of
users
that emerged over the course of the event. The network data were
analysed using
the network analysis tool Gephi (Bastian 2009). Figure 2 shows a
projection of
this network data where nodes represent users and edges represent
followships.
Edges in the network diagrams in this paper are directed and the
direction of
an edge from User A to User B implies that User B follows User A. The
edge
directions can be seen as representing the way information (in the form
of
Tweets) flows from a user to their followers.
Figure
2. The #wj25 network map showing the users that tweeted during the
event and
the followships that connect them into a network.Although in the public domain, personal user
names have been anonymised in sensitivity rather than guaranteed
anonymity.
Figure
3 shows the network map with the nodes re-sized in proportion to the
number of Tweets
that the user made over the course of the event and re-coloured in
proportion
to the number of followers the user has. Larger nodes made more Tweets
and
nodes with higher colour saturation have more followers.
Figure
3. The #wj25 network map with node size representing tweet volume
(larger nodes
indicates more Tweets) and node saturation representing followers (more
saturation indicates more followers)
Although
small, this is a very connected network, with an unsurprising
followship
commonality to the Twitter account for the Arts Festival that research
event
was part of. However there are 5 users who participated that have no
connection
to other people in the network.
The
survey questionnaire generated supplementary information about this
network’s
general use of Twitter. Certainly not all those in the screen area were
Twitter
users and those who were used it to read news and information relating
to
others, which they did 2 or 3 times as much as posting themselves.
Therefore
the online network is a small subset of those who would have seen the
screen
and projected posts since there were significant numbers of people in
the
thoroughfare who were not necessarily avid users of Twitter.
As
well as looking at followers and tweets, we examined the number of
triangles in
the graph. Eckmann and Moses (2002) define a triangle as a set of three
users
where each user in the triangle follows both of the others. The number
of
triangles is responsible for many phenomena, including the rapid (high
number
of triangles) or slow (low number of triangles) information propagation
in a network
(Eckmann and Moses 2002, Easley and Kleinberg 2010). In the case of
Twitter in
particular, the formation of a triangle guarantees higher information
exposure
since a reply from one user to another is displayed to the third user
of the
triangle as well. Therefore, the formation of triangles is a crucial
parameter
in the information exposure of the network and the analysis of our
graph.
For
the network of active users in the #wj25 network we are able to
generate the
data in Table 2. These measurements show that a significant subset of
the
active users are not only linked to one another, but also participate
in and
form more complex structures, such as triangles. Figure 4 shows the
network map
with users in triangles coloured red with the size of the node
representing the
number of Tweets.
Total active users |
35 |
Mutual Followships |
84 |
Users in a triangle |
16 |
Total triangles |
41 |
Table
2. Statistics of user
triangle formation for the #wj25 network.
Figure
4. The #wj25 network map showing users in triangles (red colour) and
their
tweet volume (size)
The
proportion of active users in triangles in this dataset may be linked
to the
formation of social, physical, ‘communities’–
such as student arts performers - and participation level of the
(active) users
during the event (Eckmann and Moses, 2002). Indeed, it can be seen from
Figure 4
that some of the more active tweeters are part of a network of
triangles, but
this is not universally the case.
The
Screen additionally mimicked the use of a hashtag for juxtaposing
comments
relating to a particular event or tangible object, in this case the
thoroughfare
that the screen and some performance events were situated in and the
Arts
Festival as a whole. In the first instance, this connects users from
disparate
or related communities, revealed if we establish membership identities
within
the network.An analysis of the network map using the algorithm
developed by
Lambiotte et al (2009) splits the network
into local communities based on the connections between neighbouring
nodes.
Applying this algorithm to the #wj25 network reveals a number of
different communities
within the network as shown in Figure 5:
Figure
5.
Communities discovered in the #wj25 network map. Four principal
communities are
identified (Yellow, Green, Red and Blue) along with one pairing (Brown)
and
independent users (pale)
Projecting
the Tweets on the giant screen mimicked the function of Twitter in
sharing
information and opinions with wider audience and followers. From
cross-referencing the survey data and an analysis of the individual
Tweet
content different types of activity can be identified.
Tweets
are mostly consistent with the user’s principal community,
supporting the
hypothesis regarding homophily – that the connections and social
acts made
through this online medium is related to the real world similarities of
interest and engagement. This is a small sample and further research
with a
larger data set may benefit from investigating this further.
Nevertheless, we
have identified clear communities within our network.As depicted in
Figure 8, users
in yellow are closely associated with the research project and tended
to
promote the event. Those in blue are closely related to the University
as staff
or societies, their Tweets tending to be marketing or commentary of
events.
Green is the largest community, based around the Student Union and the
Student
Arts Festival, posting for and about events, with a wider community in
red formed
around the fringes, representing the SoCloseToLDN online event.
Some
users took the opportunity to promote the Student Arts Festival –
either with
straightforward ‘official’ information or from a more
personal perspective,
appreciating the event & general surroundings. Cross-referencing
with the
network map shows that individuals can be prompted to contribute to
this
marketing. This is the case with at least two users, who are not
closely
connected to the Student Arts Festival like others are, but still
promote it in
both objective/informative and subjective ways:
@User16
Great atmospher at tocil fields in #warwickuni #wj25(sic)
[13:14.06]
@User23
@sandpitscreen #wj25 put on your dancing shoes and come dance with us
at
Warwick Folk’s ceilidh at 5pm in the Atrium :D [15:06.01]
SoCloseToLDN – a separate online event where members of the public could send players around London to get photographs of locations – were also aware of the potential added value of the screen, adding #wj25 to their own posts to generate interest and increase their remote audience. This is also a good example of telepresence, in that the event allowed members of the public to be ‘virtually’ in London and that this presence was projected into the thoroughfare through the screen. Other individuals used #wj25, and therefore the screen, to increase the size of their own personal and social gesture, such as saying ‘hello’ to a friend or thanking a friend for a drink.
The
literature suggests that hashtag brings Tweets together as a
‘conversation’.
The positioning of the screen in the physical space and the fact that
it
provided a window into a virtual space prompted some interesting
interaction
modalities from the users. As one user stated, it was a “fun way
to interact
without face to face chat” (Questionnaire #9). Not all posts were
positive with
users seizing the opportunity variously to share their disappointment
that TV
coverage of a tennis tournament was not being screened; deplore the
waste of
money that the Screen symbolised; and, for outlier @User11, to
criticise the
music of an outdoor concert in front of the Screen.
@User27 is an interesting example. Figure 5
shows him as part of the Student Arts Festival community, and is a user
with
many followers who tweets frequently in his daily life (see Figure 4).
On his
Twitter homepage he defines himself as an arts critic as well as a
social
critic, suggested by his background image of a recent on-campus
protest. Instead
of joining the others in marketing and personal positive promotion of
the work
of his community he instead chooses to criticise the University by his
negative
comments about the Screen. He purposefully uses the Screen itself to
further
publicise his own comment, enabling him to physically inhabit the very
space he
is challenging.
There
were also some examples of users communicating in a truly hybrid way,
interacting both with the Twitter space and the physical space through
the
medium of the screen. In these interactions information and messages
are
present on the Twitter network and also on the screen allowing people
who are
not connected to each other to see what others are posting and reply.
The game
of ‘I Spy’ started by @User8 and the photograph taking
interactions centred
around @User28 (covered below as case studies) are both examples of
information
flow in a truly hybrid space.
@User28
is an interesting example of interplay and the potential for a ripple
effect in
social behaviour. He was sat in a bar near
the screen but only became engaged when he saw another person taking a
photograph. He paid more attention to the projected text and made his
first
post:
@User28
Just want to see if this will show up #wj25
[18:46.39]
It
did, which prompted him to then take a photo of his own post on the
screen. One
of the research team, @User6, noticed his desire to interact with the
screen
and built on @User28’s own creative response, posting –
from his own Twitter
account – a photo of the photo; a playful interchange which was
reciprocated,
along with a personal recognition of the other users through the @ and
a
connection with a particular real-world community, the University
Photography Society:
Figure
6. The interplay on the
screen and the photo of a photo. This image is from the user’s
Twitter website
homepage.
Here
we have a physical act prompting a virtual act into a dialogue between
users
who do not follow one another. Eventually, another of @User28’s
followers also
joins in, trying to start a quiz. Unfortunately this was just before
the screen
was switched off and so we were unable to track subsequent acts:
@User14
@SandpitScreen #wj25 let’s play a game! Q – What turns in
to ice faster, hot or
cold water? Tweet answer to @SandpitScreen with #wj25
[19:45.39]
@User8
is another interesting case. From the network graphs it is evident that
he is
unconnected in terms of inner communities but tweeted a lot. From his
questionnaire we know that he particularly enjoys this kind of
interactive
event and posted a short farewell to the University with a sad face
emoticon in
the evening (it was the end of his last year as a student). Early on he
initiates a game of ‘I Spy’ and manages to bring several
other users in the physical
space into the interchange. It is a particular type of dialogue as its
sustainability depends not just on people using the hashtag but also
entering
content that plays within known rules. Rather than for an online
audience it is
designed for people who are occupying the same physical space and may
guess appropriately
(although that is not to say that others elsewhere could not). Even so,
within
the designs of the onscreen ‘game’, unless followers of
participating users
picked up on it and retweeted, the game would not extend very far
outside of
the immediate physical – and online – group of people.
@User8 as the originator
also gave himself particular power as he supposedly knew and could see
the
answer – in actual fact he did not start off with an answer in
mind and was
waiting for the most interesting response, exploiting his physical
anonymity. From this small case we can
see how an individual can become engaged and initiate social acts in
others
even from outlying community position. There is perhaps some attempt at
inflation of personal or social status through the use of this social
media
platform that may be worth considering in other Twitter-based research.
In
contrast to the previous two users, @SoCloseToLDN, operating
the London
based Virtual Tourist experience (Red in Figure 8), is well connected,
although
also peripheral, to the largest
community (Green in Figure 8). The userrepeatedly used #wj25 in order
to
increase audience awareness of their eventbut very few of their
associated
users did when they retweeted posts. Working on the same premise as
‘I Spy’ - that
sustainability and growth requires an investment of posts by followers
-we
assume that SoCloseToLDN’s followers were unaware of the
potential power of the
screen and of the hashtag. This is a reminder that simple opportunities
to
reach a wider audience via Twitter are not fully understood or
exploited for
whatever reason; therefore the social act does not reach the full
potential of its
impact.
Recent
literature and research highlights a need for studies that consider the
spread
of information and creation of networks across social media within a
given
temporal and spatial frame, capable of analysing at both individual and
community levels. Along with an exploration of suitable methods of
computational modelling and integrated qualitative data, such studies
will
contribute to developing our understandings of our network society. Throughout
the findings of the pilot study presented in this paper we have
provided a rich
analysis of the way in which people used Twitter and the hybrid space
through
the course of the #wj25 event.
By
combining a data-driven, network
analysis approach with a sociologically driven qualitative analysis it
is
possible to derive a deeper insight into the operation of a hybrid
network than
is possible through using one approach in isolation. We believe that
closer
studies of the Individual User – Tool (Twitter) - Other User
interface can
contribute greatly to our understanding of the possibilities for
Twitter in
social network formation and collective meaning making as users
continue to
interact with the world around them on a daily basis.
In
our analysed network, Tweets operated as objective and subjective
social acts
that promoted ideas and events, as well as made personal social
gestures. Users
subconsciously and consciously operated in a hybrid space, using the
physical
presence of the giant screen to initiate playful dialogues and power
shifts,
and to entice others as active users into the social network.
By
finding an effective way of mapping the social networkwe were able to
begin to
reveal itslevel of connectedness, and information flow through a number
of smaller
communities, as well as give a sense of more complex triangular
relationships
and homophily. This
approach, as recommended by Romero
et al (2011), has provided an analysis of the users at an individual
level
whilst also considering their place in the overall network structure.
It sits
well beside the many quantitative, impersonal approaches taken in much
of the literature
and could be expanded towards other larger studies.
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Where Age
is the time in seconds since the creation of the Tweet, and Last
Appearance is the time in seconds
since it last appeared on the screen (or equal to Age
if the Tweet has not yet been displayed). R is the
number of times the Tweet has been retweeted. H and M are the number of hashtags and mentions contained in
the Tweet
respectively. The formula was designed to ensure that new Tweets had a
high
probability of being selected. The weights applied to R¸
H, and M were designed to encourage
engagement
with other users.