DOI: 10.6084/m9.figshare.3489995.v1
title: An Archive of #DH2016 Tweets Published on Friday 15 July 2016 GMT

description: <b>Background</b><br><br>The Digital Humanities 2016 conference is taking/took place in Kraków, 
Poland, between Sunday 11 July and Saturday 16 July 2016. #DH2016 is/was
 the conference official hashtag.<br><br><b>What This Output Is</b><br><br>This
 is a CSV file containing a total
 of 4,046 Tweets publicly published with the hashtag #DH2016 on Friday 15 July 2016 GMT.<br><br>The


 archive starts with a Tweet published on Friday 15 July 2016 at 00:04:16 +0000 and ends with a Tweet published on Friday 15 July 2016
at 23:53:18 +0000 (GMT).    <br><br>Previous days have been shared on a different output. A breakdown of Tweets per day so far:<br><br>Sunday 10 July 2016: 179 Tweets<br>Monday 11 July 2016: 981 Tweets<br>Tuesday 12 July 2016: 2318 Tweets<br>Wednesday 13 July 2016: 4175 Tweets<br>Thursday 14 July 2016: 3717 Tweets<br>Friday 15 July 2016: 4046 Tweets <br> <br><b>Methodology and Limitations</b><br><br>The Tweets contained in this file were collected by Ernesto Priego using Martin Hawksey's TAGS 6.0.  <br> <br>Only
 users with at least 1 follower were included in the archive. Retweets 
have been included (Retweets count as Tweets). The collection 
spreadsheet was customised to reflect the time zone and geographical 
location of the conference.<br><br>The profile_image_url and entities_str metadata were removed before public sharing in this archive. <br><br>Please
 bear in mind that the conference hashtag has been spammed so some 
Tweets colllected may be from spam accounts. Some automated refining has
 been performed to remove Tweets not related to the conference but the 
data is likely to require further refining and deduplication.  <br><br>Both
 research and experience show that the Twitter search API is not 100% 
reliable. Large Tweet volumes affect the search collection process. The 
API might "over-represent the more central users", not offering "an 
accurate picture of peripheral activity" (Gonzalez-Bailon, Sandra, et 
al. 2012).<br><br><b>Apart from the filters and limitations already declared, it cannot be guaranteed that this file contains each and every 
Tweet tagged with #dh2016 during the indicated period, and the dataset is shared for
 archival, comparative and indicative educational research purposes only.</b><br><br>Only
 content from public accounts is included and was obtained from the 
Twitter Search API. The shared data is also publicly available to all 
Twitter users via the Twitter Search API and available to anyone with an
 Internet connection via the Twitter and Twitter Search web client and 
mobile apps without the need of a Twitter account.<br><br>Each Tweet and
 its contents were published openly on the Web with the queried hashtag 
and are responsibility of the original authors. Original Tweets are 
likely to be copyright their individual authors but please check 
individually. <br><br>No private 
personal information is shared in this dataset. The collection and 
sharing of this dataset is enabled and allowed by Twitter's Privacy 
Policy. The sharing of this dataset complies with Twitter's Developer 
Rules of the Road. <br><br>This dataset is shared to archive, document and encourage open educational research into scholarly activity on Twitter. <br><br><b>Other Considerations</b><br><br>Tweets
 published publicly by scholars during academic conferences are often 
tagged (labeled) with a hashtag dedicated to the conference in question.<br><br>The
 purpose and function of hashtags is to organise and describe 
information/outputs under the relevant label in order to enhance the 
discoverability of the labeled information/outputs (Tweets in this 
case). <br><br>A hashtag is metadata users choose freely to use so their
 content is associated, directly linked to and categorised with the 
chosen hashtag. <br><br>Though every reason for Tweeters' use of 
hashtags cannot be generalised nor predicted, it can be argued that 
scholarly Twitter users form specialised, self-selecting public 
professional networks that tend to observe scholarly practices and 
accepted modes of social and professional behaviour. <br><br>In general 
terms it can be argued that scholarly Twitter users willingly and 
consciously tag their public Tweets with a conference hashtag as a means
 to network and to promote, report from, reflect on, comment on and 
generally contribute publicly to the scholarly conversation around 
conferences. As Twitter users, conference Twitter hashtag contributors 
have agreed to Twitter's Privacy and data sharing policies.   <br><br>Professional
 associations like the Modern Language Association recognise Tweets as 
citeable scholarly outputs. Archiving scholarly Tweets is a means to 
preserve this form of rapid online scholarship that otherwise can very 
likely become unretrievable as time passes; Twitter's search API has 
well-known temporal limitations for retrospective historical search and 
collection.<br><br>Beyond individual tweets as scholarly outputs, the 
collective scholarly activity on Twitter around a conference or academic
 project or event can provide interesting insights for the contemporary 
history of scholarly communications. To date, collecting in real time is
 the only relatively accurate method to archive tweets at a small scale.
 <br><br>Though these datasets have limitations and are not thoroughly 
systematic, it is hoped they can contribute to developing new insights 
into the discipline's presence on Twitter over time.<br><br>The CC-BY license has been applied to the output in the repository as a 
curated dataset. Authorial/curatorial/collection work has been 
performed on the file in order to 
make it available as part of the scholarly record. The data contained in
 the deposited file is otherwise freely available elsewhere through 
different methods and anyone not wishing to attribute the data to the 
creator of this output is needless to say free to do their own 
collection and clean their own data.