image/svg+xml
7
IX/1/2018
InterdIscIplInarIa archaeologIca
natural scIences In archaeology
homepage: http://www.iansa.eu
Refections on the Use of Social Networking Sites as an Interactive Tool
for Data Dissemination in Digital Archaeology
Dominik Hagmann
a*
a
Department of Classical Archaeology, Faculty of Historical and Cultural Studies, University of Vienna, Franz-Klein-Gasse 1, 1190 Vienna, Austria
1. Introduction
This paper presents a case study concerning the use of
the social networking sites (SNS) Twitter, Sketchfab,
and ResearchGate as an integrated tool for digital science
communication in archaeology. Although this combination
seems to be characterised by means of a distinct heterogeneity
among the diferent SNS, the interlocking of the various sites
will be highlighted and its importance outlined. Therefore,
the basic workfow for combining a microblogging service
with a 3D content sharing site and a scientifc social
network shall be delineated within the framework of science
communication.
Disseminating data digitally can be handled in diferent
ways, both actively and passively. An active manner can be
the triggering of a social media war: in general,
war
might
be seen here as
permanent adversity
between at least two
parties. This adversity can arise for various reasons and take
diferent courses on diferent intensity levels (Kekes 2010).
Expanding the meaning of
war
to include digital conficts
within the realm of information and computer science, this
permanent adversity
can be easily combined with
social
media
, specifcally the
social web
, as an integral part of
Web
2.0
(
e.g.
Conole, Dyke, 2016; Ebersbach
et al.
, 2016, pp. 11–
33; Neal, 2012; Rheingold, 1993; O’Reilly, 2005; Stephens,
2007; Zuppo, 2012). Accordingly, war may have various
defnitions within social media: Firstly, a
social media war
may mean a public disagreement on a certain question which
is outrageously debated using social media (
e.g.
Woolston,
2015). Secondly, and more indirectly, a social media war may
also describe a fght between two or more opposing social
media services themselves (
e.g.
Ganahl, 2013). Thirdly, the
complex and quite well-known case of using social media as a
toolset for history, memory, propaganda or even as a weapon
–
in the manner of symmetric and asymmetric warfare –
has
to be considered too (
e.g.
Comunello, Anzera, 2012; Jones,
Baines, 2013; van Niekerk, Maharaj, 2013; Farwell, 2014;
Klausen, 2014; Lawson, 2014; Lähteenmäki, Virta, 2016;
Volume IX ● Issue 1/2018 ● Pages 7–20
*Corresponding author. E-mail: dominik.hagmann@univie.ac.at
ArtiCle inFo
Article history:
Received: 2
nd
January 2018
Accepted: 4
th
April 2018
DOI: http://dx.doi.org/ 10.24916/iansa.2018.1.1
Key words:
digital archaeology
public archaeology
information and communication technologies
social media
Twitter
Sketchfab
ResearchGate
open access
science communication
data dissemination
AbStrACt
Based on a case study, the paper analyses the possibilities of social media as a tool for science
communication in the context of information and communication technology (ICT) usage in
archaeology. Aside from discussing the characteristics of digital archaeology, the social networking sites
(SNS) Twitter, Sketchfab, and ResearchGate are integrated into a digital research data dissemination
tool. As a result, above-average engagement rates with few impressions were observed. Compared
with that, status updates focusing on actual feldwork and other research activities gain high numbers
of impressions with below-average engagement rates. It is believed that most of the interactions are
restricted to a core audience and that a clearly defned social media strategy is obligatory for successful
research data dissemination in archaeology, combined with regular posts in the SNS. Additionally,
active followers are of highest importance.
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Patrikarakos, 2017). Social media wars also occur in the
free web-based social messaging and microblogging service
twitter
, which is used to send short posts (so-called
tweets
)
with originally 140 characters and (since November 2017) 280
characters in some countries (
e.g.
Rosen, 2017; Richardson,
2012; 2015; Williams, Krause, 2012, pp. 105–113).
Originally, it is likely that Twitter wars (in their broadest
sense) have become a digital phenomenon in the context of
the Israeli-Palestinian confict, and thus became known to a
wider public during 2012 (Ball, 2013), considering the role
of social media in modern warfare (Sutter, 2012). Hence
Twitter war initially belongs to the above-mentioned third
defnition, incorporating the metaphysical meanings of real
and virtual war, but may have adopted additional meanings
besides. Thus, a Twitter war may also belong to the frst type
of social media war. In today’s Twitter lingo (slang) a
twitter
war
may describe in detail a quick public dialogue based on
tweets between at least two parties for several hours. The
parties involved are addressing each other mainly using the
so-called retweet- (
rt
) as well as replies- (
replying to
) and
mentions-functions (
@
) on Twitter (Twitter, 2017a; 2017b).
A quick review of last months’ tweets mentioning
the combined terms “Twitter”
and “war” reveals the
characteristics of a Twitter war in general (Twitter, 2017d).
Twitter wars seem to be declared by either one of the two
parties or even a third party without following any formal
rules. Through simply announcing an explicit statement
as well as directly mentioning the other party/parties, the
Twitter war starts. Here, one party refers to a certain position
while the other party/parties take/s an opposite one. The other
party/parties respond/s to this statement with a similar but
difering statement more or less immediately. Afterwards,
the frst party responds again,
etc
. Other recipients of the
dialogue within this Twitter war can comment on individual
tweets and may therefore be addressed by the opponents
afterwards. This special type of discussion may be conducted
as friendly banter but also as a serious debate, depending on
the parties involved.
Regarding the rhetoric of Twitter users,
#twitterwar
as well
as
#twitterWar, #twitterwar,
and
#tWitterWAr
are used,
although the term may be also used without any hashtag (
e.g.
Kehrberg, 2015; Twitter, 2017d). A hashtag thereby serves as
a freely defnable visual emphasis of the particular word, as
well as a linking tag inside the service that enables users to
flter the millions of diferent messages based on a selected
keyword by just clicking on it or searching for it (
e.g.
Bruns
et al.
, 2016; Enli, Simonsen, 2017; Small, 2011; Twitter,
2017c).
The main reason to start a Twitter war may be to stimulate
public attention on a large scale. Furthermore, a Twitter
war is a social media marketing strategy which gains the
attention of customers for all parties involved. It is important
that only equal competitors start a Twitter war and that the
involved parties treat each other with respect during the
whole confrontation (Alaimo, 2017). Otherwise a Twitter
war could quickly become something else, like a case of
internet “trolling”,
i.e.
the attempt to provoke the counterpart
and to outrage him/her, or even faming
(e.g.
Kohn, 2015).
Additionally, Twitter itself sometimes encourages such
activities (
e.g.
@TwitterNotify, 2017). Users may further
formerly invite or provoke each other to start a Twitter war
through using a matching hashtag in a corresponding post,
although this kind of request usually would not have the
desired efect.
An example of a Twitter war is the “confict” between
Denmark and Sweden in 2016: On July 7
th
, a Twitter war broke
out between the Danish Foreign Ministry and the Swedish
Institute and lasted for several hours (@denmarkdotdk, 2017;
@swendense, 2017). It all started when the Danish Foreign
Ministry quoted a post from the Swedish Institute about
special aspects of Swedish taste in interior decoration, which
primarily was meant for the amusement of the Swedish
Twitter community (@denmarkdotdk, 2016b; Podhovnik,
2016; @swendense, 2016b). The Swedes responded to that
tweet, then the Danes countered and the whole conversation
culminated into an alternating struggle for amusement
(@denmarkdotdk, 2016a; @swendense, 2016c). As the
Swedish Institute stated during the discussion repetitively,
the whole conversation was meant as “friendly rivalry”
(@swendense, 2016a).
All in all, a Twitter war may be one concept (among
others) of gaining attention of a vast group of interested
users as a frst step to sell one’s product to this target group.
It is a specialised marketing strategy which uses digital
information and communication technology (ICT) to gain
success in getting noticed. ICT is more important than ever
nowadays, mainly due to the high availability of the internet
in many parts of the world, although a serious digital divide
still exists (Cancro, 2016; Mano, 2012, pp. 30–31; Walker,
2014). Nevertheless, ICT has a very serious impact on
society, and thus the efect of ICT on archaeology can also
be observed (
e.g.
Henson, 2013).
The strategy presented here may be settled in a more
passive setting and Twitter wars are hard to fnd in the
feld of archaeology. Maybe the archaeological Twitter
community is too small and homogenous, or “big players”
within this community are not big enough for occurrences
like Twitter wars to appear regularly in archaeology.
Considering the wider feld of cultural heritage management,
a recent example from digital museology may be the Twitter
war of two British museums in 2017: On September 13
th
, in
the course of the
#AskACurator
-campaign by Mar Dixon,
another Twitter war occurred between the Science Museum
and Natural History Museum in Great Britain, because of the
question posed by Twitter user Bednarz O’Connell regarding
which museum would have the best exhibition (@bednarz,
2017a, 2017b; Dixon, 2013).
While this Twitter war was
actually started by an individual non-museologist, there are
concepts which try to facilitate mutual as well as pluralistic
activities on Twitter in archaeology, like the frst CAA
Twitter Conference (#CAATCO 2018). Furthermore, it is
questionable whether an active and possibly even aggressive
marketing concept like that conducted during a Twitter war
is suitable for archaeology.
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This paper seeks to evaluate the role of SNS regarding
their function as platforms for science communication in
the context of
digital archaeology
(
e.g.
Kansa
et al.
, 2012;
Watkins, 2016). In contrast to a Twitter war, the general
concept presented here is, in a sense, passive, because
although information is actively disseminated, it must also
be received by other Twitter users who are not actively
involved. A Twitter war, however, is active in all aspects, as
not only information is disseminated, but other users are also
actively involved. Founded on the evaluation of a case study,
it is examined whether it is necessary to start a Twitter war to
successfully disseminate information in archaeology. To do
so, recent Twitter data received from an ofcial university’s
account will be analysed.
2. Digital archaeology
Digital archaeology itself is an integral part of today’s
archaeological practice and a broad area encompassing
various aspects, methods, and ideas (
e.g.
Hagmann, 2017a;
2017b; 2017f; Langendorf
et al.
, 2017; Morgan, Eve, 2012;
Trognitz
et al.
, 2017). However, digital archaeology seems
to be neither an archaeological sub-discipline nor its own
specialisation, but rather a pool of diferent theoretical
and practical aspects of information technology and their
corresponding applications within archaeology (Costopoulos,
2016; Huggett, 2017). Applying digital methods in
archaeology expands the possibilities of creating insights
and generating knowledge (Zubrow, 2006). In this sense,
Zubrow (2006) defnes digital archaeology as the usage of
“[…] future technology to understand past behaviour […]”.
Therefore, theory and practice of combined digital input,
digital information management, digital analysis, and digital
publication
are
immanent for digital archaeology.
In regard to the above, Daly and Evans (2006) mention in
their fundamental compilation about digital archaeology that
this feld of study “[…] explores the basic relationships that
archaeologists have with Information and Communication
Technology […]” – a situation, which may be also found
in the digital humanities (
e.g.
Jannidis
et al.
, 2017). The
relationship between archaeology and ICT, as well as the
term
digital
archaeology
itself, have diferent names, such
as
archaeological informatics
(
Archäoinformatik
in some
German-speaking countries),
cyber archaeology, virtual
archaeology
, and so on (
e.g.
Djindjian, 2015; Hookk, 2016;
Levy, 2014; Reilly, 1990). There are no clear-cut borders
and, according to Grosman (2016), one can state that the
varying nomenclature is due to “many groups of scientists
worldwide, [which] almost concurrently recognized the
immense power of computer technology”. Additional digital
neighbouring “disciplines” also exist, such as the highly
independent, do-it-yourself and mainly self-funded
punk
archaeology
,
as well as
digital geoarchaeology
,
digital
history
,
digital literary history
,
digital musicology
,
or
digital
philology
(
e.g.
Ghilardi, Desruelles, 2009; Graham
et al.
,
2016; Gregory, 2014; Murrieta-Flores
et al.
, 2017; Nichols,
Altschul, 2012; Pugin, 2015; Richardson, 2017; Schofeld,
2017; Siart
et al.
, 2017).
Depending on one’s personal defnition of
archaeology
,
digital archaeology may be defned – at least in a taxonomic
view – as an integral part of the digital humanities
(
e.g.
Burdick, 2012; Warwick
et al.
, 2012). However, it seems
difcult to treat digital archaeology and digital humanities as
equivalent (
e.g.
Reiche
et al.
, 2014): considering the research
history of both felds, it seems that there are only a few
points of interaction between digital humanities and digital
archaeology. Indeed, digital archaeology may have evolved
nearly on its own (Thaller, 2017b; Zubrow, 2006, pp. 12–21).
At most, these two felds have only merged recently through
individual projects which ofer a few zones of overlap (
e.g.
dha, 2017; Kaplan, 2015). Actually, digital humanities mainly
seem to encompass varying methods of digital text analysis
in the broadest sense, the development and usage of various
database applications, open access, studies in metadata,
image classifcation research, as well as long term data
archiving (
e.g.
Bair, Carlson, 2008; Berry, 2012; DHd, 2018
Köln, 2017; Diao, Hernández, 2014; Funkhouser
et al.
, 2011;
Manovich, 2012; Röhle, 2012; Thaller, 2017a). In this case,
one should question if incorporating digital archaeology into
digital humanities would not solely be a matter of taxonomy,
regarding their highly diverse characteristics and the role of
interdisciplinarity in archaeology (
e.g.
CAA International,
2017; Hirst, 2008). However, if one defnes archaeology as
a social science instead of assigning it to the humanities or
cultural studies, these interconnections may be completely
altered again (Smith
et al.
, 2012).
Comparing digital archaeology and digital geoarchaeology
may show that these diferent digital “disciplines” are more
formally divided than they practically are. Recently, it was
claimed that the use of digital methods and applications
derived from geomatics in an archaeological context
would defne digital geoarchaeology (Siart
et al.
, 2017).
Nonetheless, spatial analysis using geographic information
systems (GIS), for example, is inherent to archaeology,
geology, geomatics, geoarchaeology, digital geoarchaeology,
as well as digital archaeology (
e.g.
Djindjian, 1998;
Schörner, Hagmann, 2015; Verhagen, 2017; Zubrow,
2006, pp. 16–21). In other words, it should be considered
if it is even possible to make a precise distinction between
a geoarchaeologist and a digital archaeologist while they
are doing feldwork and using GIS. So, it seems that such
a defnition might be valid only if rigid boundaries are
defned between these diferent felds – a state that is quite
atypical for archaeology (
e.g.
Sinclair, 2016). Moreover, the
number of disciplines using even the
same
digital methods
and tools is not limited to digital geoarchaeology and digital
archaeology. For example, digital dissemination strategies
such as open access publishing, repositories, wikis, blogs,
photo and video platforms are of highest importance for
digital archaeology as well as for nearly
all
other scientifc
disciplines nowadays (Bauer
et al.
, 2015; Morgan, 2015;
Richardson, 2017; Xia, 2012). Furthermore, the question
is if an autonomous discipline arises because of the usage
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of digital methods. One must consider if topics like ICT in
archaeology and the neighbouring branches require their
own digital archaeological disciplines and sub-disciplines,
or whether one should think of something else, especially
considering previously neglected aspects (Huggett, 2015a;
2015b).
Consequently, ICT seems to be situated in between
all
disciplines. So, digital archaeology as the theory and practice
of the complex use of ICT
throughout
archaeology may be
positioned more likely on a meta-level than being its own
specialisation or discipline. The same can be assumed for
digital zooarchaeology, digital Judaic studies, digital classics,
etc. (
e.g.
Betts
et al.
, 2011; Campbell, 2015; Schubert,
2015). One might therefore suggest that sophisticated digital
practice based on ICT within a given specialisation creates
the corresponding digital meta-discipline.
3. Research data dissemination
As mentioned above, social media have an important role
in today’s society and in archaeology (
e.g.
Gennaro, 2015;
Richardson, 2014; Rocks-Macqueen, 2016; Sedlacik, 2015;
Laracuente, 2016; Wolf, 2017). Twitter, especially, can
be regarded as an infuential SNS, serving as a platform
for individual messaging as well as for elaborate science
communication. Innovative projects like the
Public
Archaeology twitter Conference
show the high potential of
this service for science communication (#PATC 2017).
Diferent kinds of social media, such as microblogging
services like Twitter, and research networks like
Academia.edu, can be integrated for more efective outreach,
for example to enhance public reception of a newly published
research paper (
e.g.
Shuai
et al.
, 2012; Thelwall, Kousha,
2014). Going one step further, the combination of the various
abilities of social media can create a holistic digital scientifc
communication tool. Thus, it is a question of the integration
of diferent kinds of social media to form an interactive tool
for archaeological research data dissemination
–
with all its
innovations, advantages, disadvantages and problems (
e.g.
Perry, Beale, 2015; Huvila, 2013).
research data
may be
defned here as every kind of digital information available in
archaeology, including digital objects like texts, tables, and
photos, as well as ready-made publications such as research
papers and monographies (Brin
et al.
, 2013). Such a digital
archaeological communication tool is settled at a point of
disciplinary intersection and strongly overlaps with public
archaeology “[…] viewed through the lens of the internet”
(Lake, 2012, p. 476). So, the role this tool plays in digital
research data dissemination should also be considered (
e.g.
Denning, 2004; Miles, 2004). The tool may be used online,
(mainly) without restriction world-wide, interactively, and
may be comprised of numerous forms of social media, such
as online wikis, blogs, photo as well as video platforms,
and social networks (
e.g.
Scholz, 2017). Because of its
bidirectional nature, the tool allows enhanced use and reuse
of data made available on open access and other online
repositories and the sustainable publication of the meta-
data via the internet, enabling a public digital discourse and
evaluation of the data (Kansa
et al.
, 2014; Niyazov
et al.
,
2016). Through these means, the idea of open science or,
more precisely, open archaeology, can be realised (Lake,
2012; Morgan, Eve, 2012; Zhu, Purdam, 2017).
Due to the heterogenous characteristics of social media, the
SNS used should be chosen precisely: for example, Instagram,
a (primarily) mobile application, mainly focuses on photos,
videos, and GIFs and is mostly used as a sophisticated
marketing tool for individuals as well as for organisations
in various felds (
e.g.
Firsching, 2017; Moon
et al.
, 2016;
Sheldon, Bryant, 2016). Controversially, however, this SNS
is even used for e-commerce and trafcking of cultural
heritage, including human remains (Hufer, Graham, 2017).
Apart from this, Instagram is not perfectly suitable for
archaeological research data dissemination. For instance,
there is currently only the possibility of adding non-clickable
hyperlinks in combination with a single post. Without using
paid features or additional applications, clickable hyperlinks
are available on one’s so-called bio (
i.e.
personal account
description) only (Kobilke, 2016).
Twitter is arguably a more important tool for information
dissemination and communication. Posts are received very
directly and can reach wide audiences and gain numerous
interactions within a very short time. Not surprisingly,
Twitter is also extensively used in several scientifc
disciplines aside from archaeology. Here, Twitter is mainly
used for information dissemination, but also serves as a
data source for diferent types of Big Data analysis (
e.g.
Cavanillas
et al.
, 2016). Disciplines like economics,
medicine, educational research, or architecture, as well as
professionals like journalists, are using Twitter and its data,
based on the interactions of hundreds of thousands of users
and millions of data-sets to examine numerous kinds of
research questions. Examples include optimised customer
service conversations, the behaviour of people with traumatic
brain injuries, or urban land-use (
e.g.
Ahmad, 2010; Evans,
2014; Oraby
et al.
, 2017; Soliman
et al.
, 2017; Vobič
et al.
,
2016; Workewych
et al.
, 2017).
4. Methodology
Twitter is a suitable tool for specialised research data
dissemination, using hyperlinks, one of the most essential
components of the internet (Berners-Lee
et al.
, 1994; Berners-
Lee, 1997). One of these workfows is described through a
basic example here: a 3D model of trench 2/2014 from the
Roman excavation at Molino San Vincenzo in Tuscany/
Italy was uploaded to the 3D content sharing platform
Sketchfab (Hagmann
et al.
, 2015; Lloyd, 2016; Sketchfab,
2017). The model, hosted on this platform, was embedded
in a tweet: one can view the embedded model interactively
within the tweet or follow the reference to Sketchfab (@
rrl_univie, 2017c; Hagmann, Reiter, 2016c). Additional
information is provided there too and ofers further content
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through linking to other webpages, for example, the overall-
project website, Google Maps, the website of the excavation
project itself, or the author’s personal homepage (Dominik
Hagmann, 2017; Google Maps, 2017; Molino San Vincenzo,
2017; Roman Rural Landscapes, 2017). Importantly, the
data of the 3D model is provided on ResearchGate as a
data repository and linked to the model (Hagmann, Reiter,
2016a; 2016b; Kowalczyk, 2014; Thelwall, Kousha, 2015).
The data can be retrieved as 3D geometries (COLLADA)
and textures (JPEG) and all fles are citable through
digital object identifers (DOIs; Agisoft PhotoScan, 2017;
COLLADA, 2017; JPEG, 2017; DOI, 2017). ResearchGate
is used in this special case as a repository mainly because
of the high level of awareness of this platform within the
scientifc community and the possibility of assigning DOIs
to digital resources. Long-term data archiving will be
performed using the institutional repository
Phaidra
of the
University of Vienna, and it is easy to link the digital objects
on ResearchGate and Phaidra (Borrego, 2017; Jefrey, 2012;
Nicholas
et al.
, 2016; Solodovnik, Budroni, 2015; Thelwall,
Kousha, 2017; Yu
et al.
, 2016). The mentioned websites
have a (mostly) barrier-free, responsive web design and
there are mobile applications for devices like smartphones
and tablets available (
e.g.
Bernacki
et al.
, 2016; Kerkmann,
Lewandowski, 2015). These technical specifcations also
help to dissolve the digital divide, at least partially.
At the Department of Classical Archaeology at the
University of Vienna, selected (scientifc) social media
platforms are used for digital public outreach. Twitter
serves as an ofcial channel for various forms of science
communication pertaining to the research activities of a
newly established and specialised cluster of projects called
Roman Rural Landscapes (RRL). These projects mainly
focus on settlements in the Mediterranean and Central
European countryside during ancient times (
e.g.
Banks
et al.
, 2017; Gabellone, 2015; Pinfeld
et al.
, 2014; Papmehl-
Dufay, Söderström, 2017; Richardson, Dixon, 2017; Rocks-
Macqueen, 2016; Williams, Atkin, 2015; Zuanni, 2017).
Within this framework, Twitter activities started on May
15
th
, 2017, operated by the author. On December 22
nd
, 2017,
the account had a quite small audience of 165 followers.
The data-set analysed below is formed by the contents and
metrics of all tweets (n=46) from June 1
st
to September
22
nd
, 2017, retrieved from Twitter Analytics between July
31
st
and November 10
th
, 2017 (Hagmann, 2017c; Twitter
Analytics, 2017). The account had 145 followers during this
time (averaged due to slight fuctuations). The tweets mainly
contained various status updates with associated scientifc
background. 21 tweets within this period were themed to the
excavation project
Molino San Vincenzo
and thus represent
the majority of the posts (Hagmann
et al.
, 2015). Therefore,
two additional data-sets (obtained from Twitter Analytics on
September 9
th
and October 12
th
, 2017), representing the subset
of the excavation-related tweets described above, containing
all tweets (n=23) from the period August 2
nd
to August
30
th
, 2017 are also analysed (Hagmann, 2017d, 2017e).
Descriptive analysis was performed on selected qualitative
and quantitative aspects of these Twitter metrics (
e.g.
Bol,
2010): aside from the published content of the tweet as text,
general technical details like the unique identifcation number
of the tweet or the permanent URI are among them. Further
aspects, like the timestamp or the number of times how often
embedded media (photos, videos, GIFs, embedded models
etc.
) within the tweet were shared with other Twitter users
were regarded too. Attention was paid to the number of times
the tweet was shown to a Twitter user (
i.e. impressions
), as
well as the interactions (
i.e. engagements
), and the
engagement
rate
(
i.e.
the impressions divided by the engagements). For
their part, the engagements are composed of various kinds of
special actions, like retweets, replies, likes, profle clicks, link
clicks, hashtag clicks, detail expands, and media interactions
(Twitter, 2017e). No paid Twitter
Ads campaigns
for increasing
the performances of the tweets through promotion were used
– only so-called organic activities are considered (@buster,
2014; Twitter, 2017f). Aside from simple calculations, the
standard deviation (std. dev.) as well as the arithmetic mean
and median were calculated using MS Excel (Excel, 2017a;
2017b; 2017c). MS Excel and Adobe Illustrator were used
for the visualisation of the data and for generating the charts
(Adobe, 2017; Microsoft, 2017). The datasets are licensed
under a CC BY 4.0 International License (Creative Commons,
2017).
5. Results
During the period of 114 days, 46 tweets were posted,
which means 1 tweet per
c.
2.5 days on average (Figure 1):
11 tweets were posted in June, 7 tweets in July, 25 tweets in
August and 3 tweets from September 1
st
to 22
nd
, 2017. The
tweets have 609.2 (std. dev. 1140.8) impressions on average,
with a minimum of 75 and a maximum of 5497 impressions
per tweet. The average number of engagements is 12.1
(std. dev. 14.1) with a minimum of 1 and a maximum of 82
(Figure 2). The average engagement rate is 0.03 (std. dev.
0.01), or 3%, with a minimum value of 0.004 (0.4%) and
a maximum value of 0.08, respectively 8% (Figure 3). The
median engagement rate is 0.03 (3%) (Hagmann, 2017c).
Comparable values can be observed for the subset of
tweets (n=23) from August 2017, which were received from
Twitter Analytics on September 4
th
, 2017 (Figure 4): per
tweet, 784.7 (std. dev. 1349.9) impressions are recorded,
with a minimum of 105 and a maximum of 5497 shares. On
average, the tweets have 16.0 (std. dev. 18.1) engagements
(minimum: 2, maximum: 82) and a mean engagement rate
of 0.03 (std. dev. 0.01), also 3%. The minimum average
engagement rate is 0.004 (0.4%), the median engagement
rate is 0.03 (3%), the maximum average engagement rate-
value is 0.08 (8%) (Hagmann, 2017d).
Regarding impressions and engagements, the most
successful tweet, no. 892754365618028544, was published
on August 2
nd
, 2017. It is an informal status update mentioning
the preparations for the 2017 season at Molino San Vincenzo
in Tuscany. The message gained 5497 impressions and
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IANSA 2018 ● IX/1 ● 7–20
Dominik Hagmann: Refections on the Use of Social Networking Sites as an Interactive Tool for Data Dissemination in Digital Archaeology
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