This document discusses the collection and analysis of Twitter data related to the MLA conferences, emphasizing the role of citizen archivists in preserving ephemeral digital artifacts. It highlights various challenges encountered during data collection and the significance of archiving tweets for future research on scholarly communication and social networks. The presentation showcases data on tweet activity, participation, and the potential insights gained from analyzing Twitter trends in the context of academic conferences.

1. Academic excellence for business and the professions
#mla15 #s398
Butterfly Hunt:
On Collecting #mla14 Tweets
Dr Ernesto Priego
Centre for Information Science
@ernestopriego #citylis
Ernesto.Priego.1@city.ac.uk

2. #mla15 #398
#mla15
#398

3. Quickly…
• 1. Twitter data collection- “butterfly
hunt”, citizen archiving
• 2. How we collected and what we
collected
• 3. #mla14 Twitter data summary
• 4. #mla15 so far
• 5. Why Twitter data collection matters
#mla15
#398
Male
Monarch
bu4erfly
CC-­‐BY
SA
Captain-­‐tucker
Wikimedia
Commons

4. Conference Tweets Collection as Butterfly Hunt
#mla15
#398
“They
would
flu4er
toward
a
blossom,
hover
over
it.
My
bu4erfly
net
upraised,
I
stood
waiKng
only
for
the
spell
that
the
flowers
seemed
to
cast
on
the
pair
of
wings
to
have
finished
its
work,
when
all
of
a
sudden
the
delicate
body
would
glide
off
sideways
with
a
gentle
buffeKng
of
the
air,
to
cast
its
shadow
–
moKonless
as
before
–
over
another
flower,
which
just
as
suddenly
it
would
leave
without
touching.
”
(51)
Walter
Benjamin
at
the
Bibliothèque
NaKonale
de
Paris,
April
1937,
photo
by
Gisèle
Freud

5. Conference Tweet Collection as Citizen Archiving
• Citizen archivists are “the first responders
of history… arriving early on the scene to
gather, capture, describe and preserve
ephemeral artifacts of interest and helping
to ensure they survive over time to share
with the future.”
• “Almost any collection becomes interesting
once you get enough stuff in one place.”
-Butch Lazorchak, The Signal. Digital
Preservation. Library of Congress, May 8,
2013
http://blogs.loc.gov/digitalpreservation/2013/05/ian-mackaye-and-
citizen-archiving/
Screenshot
from
the
Fugazi
Live
Series
of
a
Notorious
Dallas
Concert
in
1990.

6. Data Collection; Data Sharing
• TAGS – Twitter Archiving Google Spreadsheet by Martin Hawksey
(@mhawksey)
• Not as easy as just letting it run automatically– devil is in the details
• Issues: API Limits, Spreadsheet Settings and Limits, Different Time
Zones, Spam, Character Encoding, Languages, Duplication, Bots,
Automated Tweets
• Automated methods and manual methods are required
• Online collaboration – Chris Zarate and I, across time zones,
countries, institutions
• Shared on open access repositories:
• http://bit.ly/MLA14TwitterArchive (see also
http://cdrs.columbia.edu/cdrsmain/2014/02/mla14-twitter-archive-
added-to-academic-commons/ )
#mla15
#398

7. #MLA14 Tweet Activity on Conference Days (9-12
January 2014)
#mla15
#398

8. #MLA14 Conference Days Summary
#mla15
#398

9. #MLA14 Conference Days Participation
#mla15
#398

10. #MLA14 Most Frequent Word*:
digital: 1,474 occurrences
(humanities: 1,152)
#mla15
#398
*
In
9-­‐12
January
2014
dataset,
obtained
with
Words
in
the
EnKre
Corpus,
Voyant
Tools

11. Top Ten #MLA14 user_lang*
#mla15
#398
*From
19
different
user_lang
opKons
in
dataset

12. #MLA14 Tweets and Geolocation
• Only
2%
of
Tweets
had
geolocaKon
enabled
• Of
484
Tweets
with
coordinates
in
dataset
464
were
unique
locaKons;
most
from
Chicago
metro
area
#mla15
#398

13. Why Does It Matter?
• Historical record of scholarly social media participation and an
increasingly-important manifestation of the MLA Convention activity
• Twitter is experienced “live”, as it happens, but Web and Mobile
clients do not yet allow long-term archiving of hashtag acttivity or
easier manipulation
• Tweets as ephemera; preservation for future analysis needed
• Twitter may or may not last; it may change significantly; Twitter API
rules and behaviour change very often and without warning
• Archiving and analyising Twitter evidence (data) may offer insights
into scholarly behaviour, disciplinary, thematic, linguistic and socio-
cultural trends over time, conference sentiment/feedback, for
scholarly social networks mapping, etc.
#mla15
#398

14. Thank You!
#mla15
#398
References
• Priego, Ernesto, and Zarate, Chris. “#MLA14 Twitter Archive, 9-12 January 2014”. Dataset. City
Research Online. 2014. Web.
http://openaccess.city.ac.uk/3083/ Accessed 7 January 2015.
• Priego, Ernesto. #MLA14: A First Look (I). Far Away, Yet Close. MLA Commons. 16 January 2014.
Web.http://remoteparticipation.commons.mla.org/2014/01/16/mla14-a-first-look/ Accessed 7
January 2015 (four parts).
• Priego, Ernesto. “Some Thoughts on Why You Would Like to Archive and Share [Small] Twitter
Data Sets”. 28 May 2014. Web.
https://epriego.wordpress.com/2014/05/28/some-thoughts-why-you-would-like-to-archive-and-
share-twitter-small-data/ Accessed 7 January 2015.
• Download this presentation:
http://www.slideshare.net/epriego/butterfly-hunt-on-collecting-mla14-tweets