This document summarizes a study analyzing Twitter data from several Learning Analytics and Knowledge (LAK) conferences between 2011-2015. The study found that over time, there was an extended reach of Twitter participation at the conferences, denser and more reciprocal interaction networks formed, and a wider diversity of research topics were discussed. However, there was also peripheral and inconsistent participation. The study provided an overview of descriptive analyses of the Twitter data, models of the "flow" of participants between conferences and interaction networks, and analyses of hashtags and topics discussed over time. Limitations and opportunities for future related work were also discussed.
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Lak15 Twitter Archeology
1. TWITTER ARCHEOLOGY OF
LEARNING ANALYTICS AND
KNOWLEDGE CONFERENCES
Bodong Chen, University of Minnesota
Xin (Cindy) Chen, Purdue University
Wanli Xing, University of Missouri
#LAK15, Marist College, Poughkeepsie, NY, March 20, 2015
Authors first met at the LAK14 Doctoral Consortium. Thanks, LAK!
@bodong_c
@magic_cindy
@helloworld_xing
#LAK15Meta
6. #LAK15Meta
1. When did you first tweet about #LAK?
2. Why/What do you tweet(e.g., comments, info, beer)?
3. Who did you get to know through #LAK?
4. What is your primary research topic?
7. Why “Twitter Archeology”?
● Not all have published yet
● Not all are interested in publishing
● Broader participation & richer
interactions (cf. citing)
#LAK15Meta
10. Questions
● Did Twitter enable participation and
conversation?
● Was participation persistent?
● Social dynamics & change over time?
● Underlying topics & change over time?
#LAK15Meta
11. (Cleaned) Dataset
Conference Participants Tweets
LAK11 215 1358
LAK12 606 4050
LAK13 280 2223
LAK14 362 3105
* Data wrangling challenges: inconsistencies of data shapes across years; a
systematic mistake of user ids in the 2011 archive; parsing interactions; etc.
3587 (by last night)LAK15 465
12. (Cleaned) Dataset
Conference Participants Tweets
LAK11 215 1358
LAK12 * 606 4050
LAK13 280 2223
LAK14 362 3105
* LAK12: “A substantial amount of tweets during LAK12 was about
the technologies adopted for live video streaming.”
#LAK15Meta
13. An Overview of Analyses
● Descriptive Analysis
● “Flow” of Twitter Participants
● Interaction Social Networks
● Evolution of Topics
#LAK15Meta
17. * The only reason you see a pie here is we just celebrated a big Pie Day – 3.14.15 ;)
1,217 unique
participants
Peripheral
participation
#LAK15Meta
# of years of participation
18. Interaction Networks
based on retweets,
replies and mentions
* The node size and
color are based on
betweenness centrality.
25. Types of Topics
1. Information-sharing related to
conferences and the community
2. Experience-sharing and comments
3. Specific research topics (e.g., MOOC,
assessment, students, course design)
#LAK15Meta
27. Summary
● An extended reach and increasing interactions
● Denser, more reciprocal networks
● Peripheral and in-persistent participation
● Emergence of multiple sub-communities
● Diverse & fluctuating research topics
#LAK15Meta
28. Limitations & Future Work
● Representativeness of the LAK community
● Potential loss of (earlier) data
● Challenges posed by briefness of a tweet
● Combine tweets and academic publications
● Connect/compare tweeters with authors/attendees
● Compare with other closely related communities (e.
g., EDM, LS)
● Dive into chains of conversation
Collaborative #LAK15Meta