DOI: 10.6084/m9.figshare.3749367.v2
title: #WLIC2016 Most Frequent Terms Roundup

description: <strong>I</strong>FLA stands for The International Federation of Library Associations and Institutions.
The IFLA World Library and Information Congress 2016
 and 2nd IFLA General Conference and Assembly, ‘Connections. 
Collaboration. Community’ took place 13–19 August 2016 
at the Greater Columbus Convention Center (GCCC) in Columbus, Ohio, 
United States.
The official hashtag of the conference was #WLIC2016.<br><br>This spreadsheet contains the results of a text analysis of 22327 Tweets publicly labeled with #WLIC2016 between Sunday 14 and Thursday 18 August 2015. <br><br>The collection of the source dataset was made with a Twitter Archiving Google Spreadsheet and the automated text analysis was done with the Terms tool from Voyant Tools. <br><br>The spreadsheet contains:<br><br>A sheet containing a table summarising the source archive <br><br>A sheet containing a table detailing tweet counts per day. <br><br>Sheets containing the 'raw' (no stop words, no manual refining) tables of top 300 most frequent terms and their counts for the Sun-Thu corpus and each individual corpus (1 per day).<br><br>Sheets containing the 'edited' (edited English stop word filter applied, manually refined) tables of top 50 Most frequent terms and their counts for the Sun-Thu corpus and each individual corpus (1 per day).<br><br>A sheet containing a comparison table of the top 50 per day.<br><br><b>Other Considerations</b><br><br>Only Tweets published by accounts with at least one follower were included in the source archive.<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" (González-Bailon, Sandra, et 
al, 2012).<br><br>Apart
 from the filters and limitations already declared, it cannot be 
guaranteed that each and every Tweet tagged with #WLIC2016 during the 
indicated period was analysed. The dataset was shared for archival, 
comparative and indicative educational research purposes only.<br><br>Only
 content from public accounts, obtained from the Twitter Search API, was
 analysed.  The source 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>This file contains the results of analyses of Tweets that
 were published openly on the Web with the queried hashtag; the source Tweets are not included. The content 
of the source Tweets is responsibility of the original authors. Original Tweets
 are likely to be copyright their individual authors but please check 
individually. <br><br>This work is shared to archive, document and 
encourage open educational research into scholarly activity on Twitter. 
The resulting dataset does not contain complete Tweets nor Twitter 
metadata. No private personal information was shared. The collection, 
analysis and sharing of the data has been enabled and allowed by 
Twitter's Privacy Policy. The sharing of the results complies with 
Twitter's Developer Rules of the Road. <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. 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). Tweets published 
publicly by scholars or other professionals during academic conferences 
are often publicly tagged (labeled) with a hashtag dedicated to the 
conference in question. This practice used to be the confined to a few 
'niche' fields; it is increasingly becoming the norm rather than the 
exception. <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 and the American Pyschological 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. Though this work has limitations and might not be 
thoroughly systematic, it is hoped it can contribute to developing new 
insights into a discipline's public concerns as expressed on Twitter 
over time.<br><br>As it is increasingly recommended for data sharing, the CC-0
 license has been applied to the resulting output in the repository. It 
is important however to bear in mind that some terms appearing in the 
dataset might be licensed individually differently; copyright of the 
source Tweets -and sometimes of individual terms- belongs to their authors.  <br><br>Authorial/curatorial/collection work has been performed on the
 shared file as a curated dataset resulting from analysis, in order to 
make it available as part of the scholarly record. If this dataset is 
consulted attribution is always welcome.<br>Ideally
 for proper reproducibility and to encourage other studies the whole 
archive dataset should be available.  Those wishing to obtain the whole 
Tweets should still be able to get them themselves via text and data 
mining methods.<br><br> <br><br><br>