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Finding and Representing Interesting Tweets
Jodi Schneider, Fabrizio Orlandi, Julia Anaya, Alexandre Passant
Digital Enterprise Research Institute
National University of Ireland Galway, Ireland
firstname.lastname@deri.org
Microblogging has become a popular way to
communicate, and Twitter’s popularity has grown
dramatically. Filtering is important [1]: users are
motivated to seek information [2]. 1
While Twitter’s collective value is being mined in
various ways, we lack an overall sense of the discussion
topics, concerns, and personalities of everyday users,
whose messages can be aggregated only by topic or
location. Instead of a public timeline with messages
from all users, the Twitter homepage promotes
celebrities, “Top Tweets”, and trending topics.
Interacting with people from diverse backgrounds
should be easy [3], yet Twitter users and followers tend
to be similar [4]. One of Twitter’s early successes was
in bringing users a “social sixth sense” 2 . To extend this
sense of peripheral awareness beyond a user’s own
social circle, we seek to redevelop a public stream
which is diverse yet interesting to read. We investigate
four related research questions, as follows:
1) Which tweets are consistently rated as
interesting?
2) What are the characteristics of these interesting
tweets?
3) How can we represent tweets using existing
SemanticWeb standards and activitystrea.ms?
4) How should we display interesting tweets to
users?
We collected data on 210 tweets from 42 users who
rated 10 tweets each on one of 21 questionnaires.
Tweets originated from Twitter’s public timeline API 3 ,
translated by the Google Translate API 4 .
Questionnaires, answered by 2 users, asked:
“Did you enjoy reading this tweet?” (“Yes”,
“No, because I don’t like the topic”, “No,
because I don’t know the people”, “No, because
I couldn’t understand the words”)
“What category (from [5]) best fits this tweet?”
In a formative evaluation, 10 users answered a brief
questionnaire about interfaces for displaying interesting
tweets.
36 tweets (17%), including 10 translated tweets,
were considered interesting (e.g. Table I) by both raters,
while 44 tweets (21%) were considered uninteresting by
both raters. Although we expected a correlation
between the category and the interestingness of a tweet,
1 The work presented in this paper has been funded by Science
Foundation Ireland under Grant No. SFI/08/CE/I1380 (Líon-2).
2 http://www.wired.com/techbiz/media/magazine/15-07/st_thompson
3 http://dev.twitter.com/doc/get/statuses/public timeline
4 http://translate.google.com/
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no such correlation was found. Category assignment
varied between raters, and depended on the category as
shown in Table 2.
Interesting Tweets
(followed by English translation as needed)
espere pelo mais sábio dos conselhos: o tempo !
wait for the wisest of advice: the weather!
Laat me iets gaan eten
Leave me something to eat
so it’s settled! May 8 is the day for big changes. Leaving
Tokyo! :(( but so worried for my baby2!! :((
Mom said alcohol is ur enemy, but the bible said, love ur
enemy. - @mayshaaurelia
What honors english teacher does work ONLY from out of
the text book? oh ya... mine!
Love my doctor. He hugged me at my 20lbs weight loss.
http://t.co/YEs1HuK - Al-Gaddafi International Prize for
Human Rights - errr, yeah....
Zac Brown Band....i love you
follow @Rebecca Jade x she is an amazing person
Table 1 A Selection of Interesting Tweets
Agreed Disagreed
Category
Tweets Tweets
1 12 Anecdote (AN)
23 51 Information Sharing (IS)
12 38 Me now (ME)
8 36 Opinions/Complaints (OC)
3 16 Presence Maintenance
5 10 Question to followers (QF)
4 18 Self Promotion (SP)
20 68 Statements and Random Thoughts
(RT)
Table 2 Tweet Categories
References
[1] D. Ramage, S. Dumais, and D. Liebling, “Characterizing
microblogs with topic models,” in ICWSM, 2010.
[2] P. Johnson and S. Yang, “Uses and gratifications of
Twitter,” in AEJMC, 2009.
[3] S. Yardi and d. boyd, “Dynamic Debates,” Bulletin of
Science, Technology & Society, vol. 30, no. 5, p. 316, 2010.
[4] M. Smith and C. Giraud-Carrier, “Bonding vs. Bridging
Social Capital,” in ICWSM, 2010.
[5] M. Naaman, J. Boase, and C. Lai, “Is it really about me?:
Message content in social awareness streams,” in CSCW ’10,
2010.