An Archive of #DH2016 Tweets Published on Friday 15 July 2016 GMT

<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.

**背景**

2016年人文数字会议（Digital Humanities 2016，下称DH2016）于2016年7月11日周日至7月16日周六在波兰克拉科夫举办。#DH2016是本次会议的官方话题标签（hashtag）。

**本数据集说明**

本文件为逗号分隔值（CSV）格式，共收录4046条于2016年7月15日周五格林尼治标准时间（GMT）以话题标签#DH2016公开发布的推文（Tweets）。

本存档的第一条推文发布于2016年7月15日周五00:04:16 +0000，最后一条推文发布于2016年7月15日周五23:53:18 +0000（GMT）。

此前日期的推文已通过其他渠道发布。截至目前各日期推文统计如下：

2016年7月10日周日：179条推文
2016年7月11日周一：981条推文
2016年7月12日周二：2318条推文
2016年7月13日周三：4175条推文
2016年7月14日周四：3717条推文
2016年7月15日周五：4046条推文

**采集方法与局限性**

本文件收录的推文由Ernesto Priego通过Martin Hawksey开发的TAGS 6.0工具采集。

本次采集仅纳入拥有至少1名粉丝的用户发布的内容，转发推文（Retweets）亦被计入推文总数。采集所用的电子表格已针对本次会议的时区与地理位置进行定制。

本存档在公开发布前已移除profile_image_url与entities_str元数据。

请注意，本次会议的话题标签曾遭遇垃圾信息攻击，因此部分收录推文可能来自垃圾账号。采集过程中已进行初步自动化筛选以剔除与会议无关的推文，但本数据集仍需进一步清理与去重。

已有研究与实践经验表明，Twitter搜索API（Twitter Search API）并非100%可靠。推文的大规模发布会影响采集流程，该API可能“过度呈现核心用户”，无法“准确反映边缘用户的活动”（Gonzalez-Bailon, Sandra, et al. 2012）。

除上述已声明的筛选规则与局限性外，本文件无法保证收录了指定时间段内所有带有#dh2016标签的推文，本数据集仅用于存档、对比与示范性教育研究。

本数据集仅收录公开账号发布的内容，数据来源于Twitter搜索API。所有Twitter用户均可通过Twitter搜索API获取该公开数据，任何拥有互联网连接的用户无需Twitter账号即可通过Twitter官网、Twitter搜索网页客户端及移动应用访问相关内容。

每条推文及其内容均为原作者在网络上公开发布的、带有指定话题标签的内容，其法律责任由原作者承担。原始推文的版权归各自作者所有，请另行核实。

本数据集未包含任何私人个人信息。本数据集的采集与发布符合Twitter隐私政策，同时遵循Twitter开发者行为准则。

本数据集旨在存档、记录并推动针对Twitter平台上学术活动的开放教育研究。

**其他注意事项**

学者在学术会议期间公开发布的推文通常会使用对应会议的专属话题标签进行标注。

话题标签的作用与功能在于将信息/内容归类至相关标签下，以提升标注信息（本场景下为推文）的可发现性。

话题标签是用户自主选择添加的元数据，用于将发布内容与选定的话题标签关联、直接链接并归类。

尽管无法全面概括或预判推文用户使用话题标签的全部动机，但可以认为，学术Twitter用户形成了专业化、自主选择的公共专业网络，且通常遵循学术规范与公认的社交及职业行为模式。

总体而言，学术Twitter用户会主动、有意识地使用会议话题标签标注其公开推文，以此构建学术社交网络、推广研究成果、现场报道会议、反思会议内容、发表评论，并从整体上参与围绕会议的学术对话。作为Twitter用户，使用会议话题标签发布推文的参与者已同意遵守Twitter的隐私与数据共享政策。

现代语言协会（Modern Language Association）等专业协会已将推文列为可引用的学术成果。存档学术推文是保存这类快速在线学术成果的有效方式，否则随着时间推移，这类成果很可能无法再被检索到——Twitter搜索API在回溯性历史检索与采集中存在众所周知的时效性限制。

除作为学术成果的单条推文外，围绕会议、学术项目或活动在Twitter上产生的集体学术活动，可为学术传播的当代史提供有趣的研究视角。截至目前，实时采集是小规模存档推文的唯一相对准确的方法。

尽管本类数据集存在局限性且未经过严格的系统性处理，但仍希望其可为研究该学科在Twitter平台上的长期发展提供新的视角。

本仓库中的数据集已采用知识共享署名（CC-BY）许可证进行授权。本文件经过作者/策展人/采集者的整理加工，以作为学术记录的一部分对外发布。本存档文件中的数据亦可通过其他途径免费获取，任何不愿将数据归因于本数据集创作者的用户，均可自行进行数据采集与清理工作。