Determining Whether and When People Participate in the Events They Tweet About Page: 641
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Determining Whether and When People Participate
in the Events They Tweet About
Krishna C. Sanagavarapu, Alakananda Vempala and Eduardo Blanco
Human Intelligence and Language Technologies Lab
University of North Texas
Denton, TX, 76203
{KrishnaSanagavarapu,AlakanandaVempala}@my.unt.edu, eduardo.blanco@unt.eduAbstract
This paper describes an approach to de-
termine whether people participate in the
events they tweet about. Specifically, we
determine whether people are participants
in events with respect to the tweet times-
tamp. We target all events expressed by
verbs in tweets, including past, present and
events that may occur in the future. We
present new annotations using 1,096 event
mentions, and experimental results show-
ing that the task is challenging.
1 Introduction
Twitter has quickly become one of the most popu-
lar social media sites: it has 313 million monthly
active users, and 500 million tweets are published
daily. People tweet about breaking news, world
and local events (e.g., eclipses, road closures), and
personal events ranging from important life events
(e.g., graduating from college) to mundane events
such as commuting and attending a party.
People tweet not only about events in which
they participate, but also events in which they
do not participate but are somehow relevant (e.g.,
John Doe may tweet about his nephew graduating
from college). More specifically, people can par-
ticipate in the events they tweet about (underlining
indicates events of interest below) prior to tweet-
ing (e.g., When I come back to London, I realise
how much I miss living here), while tweeting (e.g.,
Nope. Not yet. Still in my car enjoying traffic),
or after tweeting (e.g., Can't wait to fly home this
summer). In the third example, it is not guaran-
teed that fly will occur, so one can only say that
the author will probably participate in fly.
In this paper, we determine whether people par-
ticipate in the events they tweet about. More
specifically, we determine whether they are par-ticipants before tweeting, while tweeting and after
tweeting, and define event participants as people
directly involved in an event, regardless of whether
they are the agent, recipient or play another role.
The main contributions of this paper are: (a) an-
notations using 1,096 events from 826 tweets; (b)
analysis showing that authors of tweets are often
not participants in the events they tweet about be-
fore or after tweeting; and (c) experimental results
showing that the task can be automated.
2 Previous Work
Most previous efforts on detecting events from
Twitter focus on events of general importance
(e.g., death of a celebrity, natural disasters) or ma-
jor life events of individuals (e.g. John Doe getting
married, having a baby, being promoted).
Extracting events of general importance often
includes extracting the entities involved, date and
location, and classifying events into classes such
as trial, product launch or death (Ritter et al.,
2012). Exploiting redundancy in tweets to ex-
tract events is common (Zhou et al., 2014), as well
as spatio-temporal information (Cheng and Wicks,
2014), i.e., when and where tweets originate from.
Extracting major life events consists on pin-
pointing significant events from mundane events
(e.g., having lunch, exercising) (Di Eugenio et al.,
2013; Li et al., 2014; Dickinson et al., 2015), and
determining whether significant events are rele-
vant to Twitter users (e.g., Why doesn't John marry
Mary already? [not relevant to the author]).
Unlike these previous efforts, the work pro-
posed here determines whether people participate
in the events they tweet about, and specifies when
with respect to tweet timestamps. As a result,
we target past events, ongoing events, and events
likely to occur in the future. Additionally, we tar-
get all events regardless of importance.
)41Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Short Papers), pages 641-646
Vancouver, Canada, July 30 - August 4, 2017. 2017 Association for Computational Linguistics
https://doi.org/10.18653/vl/P17-2101
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Sanagavarapu, Krishna C.; Vempala, Alakananda & Blanco, Eduardo. Determining Whether and When People Participate in the Events They Tweet About, article, August 2017; Stroudsburg, Pennsylvania. (https://digital.library.unt.edu/ark:/67531/metadc991029/m1/1/?rotate=270: accessed July 18, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Engineering.