Hi all,
The next Research Showcase will be live-streamed next Wednesday, February
16, at 9:30 PT/17:30 UTC. The theme is: Collective Attention in Wikipedia.
YouTube stream:
https://www.youtube.com/watch?v=bg2aE2m08Qo
As usual, you can join the conversation on IRC at #wikimedia-research. You
can also watch our past research showcases here:
https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase
The Showcase will feature the following talks:
Modeling Collective Anticipation and Response on WikipediaBy *Renaud
Lambiotte <https://www.maths.ox.ac.uk/people/renaud.lambiotte> (University
of Oxford)*The dynamics of popularity in online media are driven by a
combination of endogenous spreading mechanisms and response to exogenous
shocks including news and events. However, little is known about the
dependence of temporal patterns of popularity on event-related information,
e.g. which types of events trigger long-lasting activity. Here we propose a
simple model that describes the dynamics around peaks of popularity by
incorporating key features, i.e., the anticipatory growth and the decay of
collective attention together with circadian rhythms. The proposed model
allows us to develop a new method for predicting the future page view
activity and for clustering time series. To validate our methodology, we
collect a corpus of page view data from Wikipedia associated to a range of
planned events, that are events which we know in advance will have a fixed
date in the future, such as elections and sport events. Our methodology is
superior to existing models in both prediction and clustering tasks.
Furthermore, restricting to Wikipedia pages associated to association
football, we observe that the specific realization of the event, in our
case which team wins a match or the type of the match, has a significant
effect on the response dynamics after the event. Our work demonstrates the
importance of appropriately modeling all phases of collective attention, as
well as the connection between temporal patterns of attention and
characteristic underlying information of the events they represent.
Sudden Attention Shifts on Wikipedia During the COVID-19 CrisisBy *Kristina
Gligorić <https://kristinagligoric.github.io/> (EPFL)*We study how the
COVID-19 pandemic, alongside the severe mobility restrictions that ensued,
has impacted information access on Wikipedia, the world’s largest online
encyclopedia. A longitudinal analysis that combines pageview statistics for
12 Wikipedia language editions with mobility reports published by Apple and
Google reveals massive shifts in the volume and nature of information
seeking patterns during the pandemic. Interestingly, while we observe a
transient increase in Wikipedia’s pageview volume following mobility
restrictions, the nature of information sought was impacted more
permanently. These changes are most pronounced for language editions
associated with countries where the most severe mobility restrictions were
implemented. We also find that articles belonging to different topics
behaved differently; e.g., attention towards entertainment-related topics
is lingering and even increasing, while the interest in health- and
biology-related topics was either small or transient. Our results highlight
the utility of Wikipedia for studying how the pandemic is affecting
people’s needs, interests, and concerns.
--
Emily Lescak (she / her)
Senior Research Community Officer
The Wikimedia Foundation